@proceedings {7110,
	title = {The Algebraic Path Problem for Graph Metrics},
	volume = {162},
	year = {2022},
	pages = {19178-19204},
	author = {Fita , E and Damrich, S. and Hamprecht, F A}
}
@phdthesis {7109,
	title = {Discovering Structure without Labels},
	year = {2022},
	author = {Damrich, S}
}
@article {7049,
	title = {Visualizing hierarchies in scRNA-seq data using a density tree-biased autoencoder},
	journal = {Bioinformatics},
	volume = {38 (Suppl 1)},
	number = { arXiv:2102.05892},
	year = {2022},
	pages = {i316-i324},
	publisher = {arXiv preprint},
	doi = {10.1093/bioinformatics/btac249 },
	author = {Garrido, Q and Damrich, S and J{\"a}ger, A and Cerletti, D and Claassen, M and Najman, L and Hamprecht, F A}
}
@proceedings {7044,
	title = {Behavior-Driven Synthesis of Human Dynamics},
	year = {2021},
	url = {https://arxiv.org/abs/2103.04677},
	author = {Andreas Blattmann and Timo Milbich and Michael Dorkenwald and Bj{\"o}rn Ommer}
}
@proceedings {7084,
	title = {Directed Probabilistic Watershed},
	volume = {34},
	year = {2021},
	author = {Fita, E and Damrich, S and Hamprecht, FA}
}
@conference {7068,
	title = {iPOKE: Poking a Still Image for Controlled Stochastic Video Synthesis},
	booktitle = {Proceedings of the International Conference on Computer Vision (ICCV)},
	year = {2021},
	url = {https://arxiv.org/abs/2107.02790},
	author = {Andreas Blattmann and Timo Milbich and Michael Dorkenwald and Bj{\"o}rn Ommer}
}
@techreport {7050,
	title = {ISTDECO: In Situ Transcriptomics Decoding by Deconvolution},
	year = {2021},
	institution = {bioRxiv},
	author = {Andersson, A and Diego, F and Hamprecht, F A and W{\"a}hlby, C}
}
@conference {6992,
	title = {Learning Multi-Scale Photo Exposure Correction},
	booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
	year = {2021},
	url = {https://arxiv.org/abs/2003.11596},
	author = {Mahmoud Afifi and Konstantinos G Derpanis and Bj{\"o}rn Ommer and Michael S Brown}
}
@proceedings {7033,
	title = {MultiStar: Instance Segmentation of Overlapping Objects with Star-Convex Polygons},
	year = {2021},
	pages = {295-298},
	doi = {10.1109/ISBI48211.2021.9433769},
	author = {Walter, F C and Damrich, S and Hamprecht, FA}
}
@unpublished {7088,
	title = {Seipin forms a flexible cage at lipid droplet formation sites},
	year = {2021},
	publisher = {bioRxiv},
	doi = {10.1101/2021.08.05.45527},
	author = {Arlt, H and Sui, X and Folger, B and Adams, C and Chen, X and Remme, R and Hamprecht, FA and DiMaio, F and Liao, M and Goodman, JM and Farese, RV and Walther, TC}
}
@proceedings {7031,
	title = {Shape or Texture: Understanding Discriminative Features in CNNs},
	year = {2021},
	author = {Md Amirul Islam and Matthew Kowal and Patrick Esser and Sen Jia and Bj{\"o}rn Ommer and Konstantinos G Derpanis and Neil Bruce}
}
@proceedings {7053,
	title = {Stochastic Image-to-Video Synthesis usin cINNs},
	year = {2021},
	author = {Michael Dorkenwald and Timo Milbich and Andreas Blattmann and Robin Rombach and Konstantinos G. Derpanis and Bj{\"o}rn Ommer}
}
@article {7048,
	title = {UMAP does not reproduce high-dimensional similarities due to negative sampling},
	number = {arXiv:2103.14608},
	year = {2021},
	publisher = {arXiv preprint},
	author = {Damrich, S and Hamprecht, F.H.}
}
@proceedings {7085,
	title = {On UMAP{\textquoteright}s True Loss Function},
	volume = {34},
	year = {2021},
	author = {Damrich, S and Hamprecht, FA}
}
@proceedings {7063,
	title = {Understanding Object Dynamics for Interactive Image-to-Video Synthesis},
	year = {2021},
	abstract = {What would be the effect of locally poking a static scene? We present an approach that learns naturally-looking global articulations caused by a local manipulation at a pixel level. Training requires only videos of moving objects but no information of the underlying manipulation of the physical scene. Our generative model learns to infer natural object dynamics as a response to user interaction and learns about the interrelations between different object body regions. Given a static image of an object and a local poking of a pixel, the approach then predicts how the object would deform over time. In contrast to existing work on video prediction, we do not synthesize arbitrary realistic videos but enable local interactive control of the deformation. Our model is not restricted to particular object categories and can transfer dynamics onto novel unseen object instances. Extensive experiments on diverse objects demonstrate the effectiveness of our approach compared to common video prediction frameworks.},
	url = {https://arxiv.org/abs/2106.11303v1},
	author = {Andreas Blattmann and Timo Milbich and Michael Dorkenwald and Bj{\"o}rn Ommer}
}
@article {7045,
	title = {Unsupervised behaviour analysis and magnification (uBAM) using deep learning},
	journal = {Nature Machine Intelligence},
	year = {2021},
	abstract = {Motor behaviour analysis is essential to biomedical research and clinical diagnostics as it provides a non-invasive strategy for identifying motor impairment and its change caused by interventions. State-of-the-art instrumented movement analysis is time- and cost-intensive, because it requires the placement of physical or virtual markers. As well as the effort required for marking the keypoints or annotations necessary for training or fine-tuning a detector, users need to know the interesting behaviour beforehand to provide meaningful keypoints. Here, we introduce unsupervised behaviour analysis and magnification (uBAM), an automatic deep learning algorithm for analysing behaviour by discovering and magnifying deviations. A central aspect is unsupervised learning of posture and behaviour representations to enable an objective comparison of movement. Besides discovering and quantifying deviations in behaviour, we also propose a generative model for visually magnifying subtle behaviour differences directly in a video without requiring a detour via keypoints or annotations. Essential for this magnification of deviations, even across different individuals, is a disentangling of appearance and behaviour. Evaluations on rodents and human patients with neurological diseases demonstrate the wide applicability of our approach. Moreover, combining optogenetic stimulation with our unsupervised behaviour analysis shows its suitability as a non-invasive diagnostic tool correlating function to brain plasticity.},
	doi = {https://doi.org/10.1038/s42256-021-00326-x},
	url = {https://rdcu.be/ch6pL},
	author = {Biagio Brattoli and Uta B{\"u}chler and Michael Dorkenwald and Philipp Reiser and Linard Filli and Fritjof Helmchen and Anna-Sophia Wahl and Bj{\"o}rn Ommer}
}
@article {7090,
	title = {Accurate and Versatile 3D Segmentation of Plant Tissues at Cellular Resolution},
	journal = {eLife},
	volume = {9},
	year = {2020},
	doi = {10.7554/eLife.57613},
	author = {Wolny, A and Cerrone, L and Vijayan, A and Tofanelli, R and Vilches-Barro, A and Louveaux, M and Wenzel, C and Strauss, S and Wilson-Sanchez, D and Lymbouridou, R and Steigleder, SS and Pape, C and Bailoni, A and Duran-Nebreda, S and Bassel, GW and Lohmann, JU and Tsiantis, M and Hamprecht, FA and Schneitz, K and Maizel, A and Kreshuk, A}
}
@article {7029,
	title = {Deep learning of cuneiform sign detection with weak supervision using transliteration alignment},
	journal = {PLoS ONE},
	volume = {15},
	year = {2020},
	month = {12/2020},
	type = {Journal},
	chapter = {1-21},
	abstract = {The cuneiform script provides a glimpse into our ancient history. However, reading age-old clay tablets is time-consuming and requires years of training. To simplify this process, we propose a deep-learning based sign detector that locates and classifies cuneiform signs in images of clay tablets. Deep learning requires large amounts of training data in the form of bounding boxes around cuneiform signs, which are not readily available and costly to obtain in the case of cuneiform script. To tackle this problem, we make use of existing transliterations, a sign-by-sign representation of the tablet content in Latin script. Since these do not provide sign localization, we propose a weakly supervised approach: We align tablet images with their corresponding transliterations to localize the transliterated signs in the tablet image, before using these localized signs in place of annotations to re-train the sign detector. A better sign detector in turn boosts the quality of the alignments. We combine these steps in an iterative process that enables training a cuneiform sign detector from transliterations only. While our method works weakly supervised, a small number of annotations further boost the performance of the cuneiform sign detector which we evaluate on a large collection of clay tablets from the Neo-Assyrian period. To enable experts to directly apply the sign detector in their study of cuneiform texts, we additionally provide a web application for the analysis of clay tablets with a trained cuneiform sign detector.},
	keywords = {cuneiform script, deep learning, sign detection, Weakly supervised learning},
	doi = {https://doi.org/10.1371/journal.pone.0243039},
	url = {https://hci.iwr.uni-heidelberg.de/compvis/projects/cuneiform},
	author = {Tobias Dencker and Pablo Klinkisch and Stefan M Maul and Bj{\"o}rn Ommer}
}
@conference {Cvpr2020,
	title = {Self-Supervised Viewpoint Learning From Image Collections},
	booktitle = {CONSAC},
	year = {2020},
	abstract = {Training deep neural networks to estimate the viewpoint of objects requires large labeled training datasets. However, manually labeling viewpoints is notoriously hard, error-prone, and time-consuming. On the other hand, it is relatively easy to mine many unlabelled images of an object category from the internet, e.g., of cars or faces. We seek to answer the research question of whether such un-labeled collections of in-the-wild images can be successfully utilized to train viewpoint estimation networks for general object categories purely via self-supervision. Self-supervision here refers to the fact that the only true supervisory signal that the network has is the input image itself. We propose a novel learning framework which incorporates an analysis-by-synthesis paradigm to reconstruct images in a viewpoint aware manner with a generative network, along with symmetry and adversarial constraints to successfully supervise our viewpoint estimation network. We show that our approach performs competitively to fully-supervised approaches for several object categories like human faces, cars, buses, and trains. Our work opens up further research in self-supervised viewpoint learning and serves as a robust baseline for it. We open-source our code at https://github.com/NVlabs/SSV .},
	url = {https://github.com/NVlabs/SSV},
	author = {S.K. Mustikovela and V. Jampani and S. De Mello and S. Liu and U. Iqbal and C. Rother and J. Kautz}
}
@article {Desana:2020aa,
	title = {Sum-Product Graphical Models},
	journal = {Machine Learning},
	volume = {109},
	number = {1},
	year = {2020},
	pages = {135{\textendash}173},
	author = {Desana, M. and Schn{\"o}rr, C.}
}
@proceedings {7042,
	title = {Unsupervised Magnification of Posture Deviations Across Subjects},
	year = {2020},
	author = {Michael Dorkenwald and Uta B{\"u}chler and Bj{\"o}rn Ommer}
}
@article {6290,
	title = {Bolus arrival time estimation in dynamic contrast-enhanced magnetic resonance imaging of small animals based on spline models, in press},
	journal = {Physics in Medicine and Biology},
	volume = {64},
	year = {2019},
	doi = {http://iopscience.iop.org/article/10.1088/1361-6560/aafce7},
	author = {Bendinger, AL and Debus, C and Glowa, C and Karger, CP and Peter, J and Martin Storath}
}
@article {Kleesiek2019,
	title = {Can Virtual Contrast Enhancement in Brain MRI Replace Gadolinium?: A Feasibility Study},
	journal = {Investigative Radiology},
	volume = {54},
	year = {2019},
	pages = {653{\textendash}660},
	abstract = {Objectives Gadolinium-based contrast agents (GBCAs) have become an integral part in daily clinical decision making in the last 3 decades. However, there is a broad consensus that GBCAs should be exclusively used if no contrast-free magnetic resonance imaging (MRI) technique is available to reduce the amount of applied GBCAs in patients. In the current study, we investigate the possibility of predicting contrast enhancement from noncontrast multiparametric brain MRI scans using a deep-learning (DL) architecture. Materials and Methods A Bayesian DL architecture for the prediction of virtual contrast enhancement was developed using 10-channel multiparametric MRI data acquired before GBCA application. The model was quantitatively and qualitatively evaluated on 116 data sets from glioma patients and healthy subjects by comparing the virtual contrast enhancement maps to the ground truth contrast-enhanced T1-weighted imaging. Subjects were split in 3 different groups: Enhancing tumors (n = 47), nonenhancing tumors (n = 39), and patients without pathologic changes (n = 30). The tumor regions were segmented for a detailed analysis of subregions. The influence of the different MRI sequences was determined. Results Quantitative results of the virtual contrast enhancement yielded a sensitivity of 91.8\% and a specificity of 91.2\%. T2-weighted imaging, followed by diffusion-weighted imaging, was the most influential sequence for the prediction of virtual contrast enhancement. Analysis of the whole brain showed a mean area under the curve of 0.969 {\textpm} 0.019, a peak signal-to-noise ratio of 22.967 {\textpm} 1.162 dB, and a structural similarity index of 0.872 {\textpm} 0.031. Enhancing and nonenhancing tumor subregions performed worse (except for the peak signal-to-noise ratio of the nonenhancing tumors). The qualitative evaluation by 2 raters using a 4-point Likert scale showed good to excellent (3-4) results for 91.5\% of the enhancing and 92.3\% of the nonenhancing gliomas. However, despite the good scores and ratings, there were visual deviations between the virtual contrast maps and the ground truth, including a more blurry, less nodular-like ring enhancement, few low-contrast false-positive enhancements of nonenhancing gliomas, and a tendency to omit smaller vessels. These "features" were also exploited by 2 trained radiologists when performing a Turing test, allowing them to discriminate between real and virtual contrast-enhanced images in 80\% and 90\% of the cases, respectively. Conclusions The introduced model for virtual gadolinium enhancement demonstrates a very good quantitative and qualitative performance. Future systematic studies in larger patient collectives with varying neurological disorders need to evaluate if the introduced virtual contrast enhancement might reduce GBCA exposure in clinical practice.},
	keywords = {Bayesian uncertainty, deep learning, gadolinium-based contrast agents, glioma, multiparametric MRI},
	issn = {15360210},
	doi = {10.1097/RLI.0000000000000583},
	author = {Kleesiek, Jens and Morshuis, Jan Nikolas and Isensee, Fabian and Deike-Hofmann, Katerina and Paech, Daniel and Kickingereder, Philipp and K{\"o}the, Ullrich and Rother, Carsten and Forsting, Michael and Wick, Wolfgang and Bendszus, Martin and Schlemmer, Heinz Peter and Radbruch, Alexander}
}
@conference {Mackowiak2019,
	title = {CEREALS - Cost-Effective REgion-based Active Learning for Semantic Segmentation},
	booktitle = {British Machine Vision Conference 2018, BMVC 2018},
	year = {2019},
	abstract = {State of the art methods for semantic image segmentation are trained in a supervised fashion using a large corpus of fully labeled training images. However, gathering such a corpus is expensive, due to human annotation effort, in contrast to gathering unlabeled data. We propose an active learning-based strategy, called CEREALS, in which a human only has to hand-label a few, automatically selected, regions within an unlabeled image corpus. This minimizes human annotation effort while maximizing the performance of a semantic image segmentation method. The automatic selection procedure is achieved by: a) using a suitable information measure combined with an estimate about human annotation effort, which is inferred from a learned cost model, and b) exploiting the spatial coherency of an image. The performance of CEREALS is demonstrated on Cityscapes, where we are able to reduce the annotation effort to 17\%, while keeping 95\% of the mean Intersection over Union (mIoU) of a model that was trained with the fully annotated training set of Cityscapes.},
	author = {Mackowiak, Radek and Lenz, Philip and Ghori, Omair and Ferran Diego and Lange, Oliver and Carsten Rother}
}
@proceedings {6288,
	title = {LeMoNADe: Learned Motif and Neuronal Assembly Detection in calcium imaging videos},
	year = {2019},
	author = {Kirschbaum, E. and Manuel Hau{\ss}mann and Wolf, S and Sonntag, H and Schneider, J and Elzoheiry, S and Kann, O and Durstewitz, D and Fred A. Hamprecht}
}
@article {6315,
	title = {A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms},
	journal = {arXiv preprint arXiv:1901.10912},
	year = {2019},
	author = {Bengio, Y and Deleu, T and Rahaman, N and Ke, R and Lachapelle, S and Bilaniuk, O and Goyal, A and Pal, C}
}
@conference {fita2019probabilistic,
	title = {Probabilistic Watershed: Sampling all spanning forests for seeded segmentation and semi-supervised learning},
	booktitle = {Advances in Neural Information Processing Systems},
	year = {2019},
	author = {Fita Sanmartin, E and Damrich, Sebastian and Hamprecht, Fred A.}
}
@article {Desana:2019aa,
	title = {Sum-Product Graphical Models},
	journal = {Machine Learning},
	year = {2019},
	url = {https://doi.org/10.1007/s10994-019-05813-2},
	author = {Desana, M. and Schn{\"o}rr, C.}
}
@article {6337,
	title = {Total variation regularization of pose signals with an application to 3D freehand ultrasound},
	journal = {IEEE Transactions on Medical Imaging},
	volume = {38(10)},
	year = {2019},
	pages = {2245-2258},
	doi = { 10.1109/TMI.2019.2898480},
	author = {Esposito, M and Hennersperger, C and G{\"o}bl, R and Demaret, L and Martin Storath and Navab, N and Baust, M and Weinmann, A}
}
@conference {Hodan2018,
	title = {BOP: Benchmark for 6D object pose estimation},
	booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
	volume = {11214 LNCS},
	year = {2018},
	month = {aug},
	pages = {19{\textendash}35},
	abstract = {We propose a benchmark for 6D pose estimation of a rigid object from a single RGB-D input image. The training data consists of a texture-mapped 3D object model or images of the object in known 6D poses. The benchmark comprises of: (i) eight datasets in a unified format that cover different practical scenarios, including two new datasets focusing on varying lighting conditions, (ii) an evaluation methodology with a pose-error function that deals with pose ambiguities, (iii) a comprehensive evaluation of 15 diverse recent methods that captures the status quo of the field, and (iv) an online evaluation system that is open for continuous submission of new results. The evaluation shows that methods based on point-pair features currently perform best, outperforming template matching methods, learning-based methods and methods based on 3D local features. The project website is available at bop.felk.cvut.cz.},
	isbn = {9783030012489},
	issn = {16113349},
	doi = {10.1007/978-3-030-01249-6_2},
	url = {http://arxiv.org/abs/1808.08319},
	author = {Hoda{\v n}, Tom{\'a}{\v s} and Michel, Frank and Brachmann, Eric and Kehl, Wadim and Buch, Anders Glent and Kraft, Dirk and Drost, Bertram and Vidal, Joel and Ihrke, Stephan and Zabulis, Xenophon and Sahin, Caner and Manhardt, Fabian and Tombari, Federico and Kim, Tae Kyun and Matas, Ji{\v r}{\'\i} and Carsten Rother}
}
@mastersthesis {6274,
	title = {The Energy Landscape of Deep Neural Networks},
	year = {2018},
	school = {Heidelberg University},
	author = {Draxler, F}
}
@proceedings {6272,
	title = {Essentially No Barriers in Neural Network Energy Landscape},
	volume = {80},
	year = {2018},
	pages = {1308--1317},
	author = {Draxler, F and Veschgini, K and Salmhofer, M and Fred A. Hamprecht}
}
@conference {6250,
	title = {Learning to Forecast Pedestrian Intention from Pose Dynamics},
	booktitle = {Intelligent Vehicles, IEEE, 2018},
	year = {2018},
	author = {Omar Ghori and Radek Mackowiak and Miguel Bautista and Niklas Beuter and Lucas Drumond and Ferran Diego and Bj{\"o}rn Ommer}
}
@conference {vianello2018,
	title = {Robust Hough transform based 3D reconstruction from circular light fields},
	booktitle = {Conference on Computer Vision and Pattern Recognition (CVPR)},
	year = {2018},
	doi = {10.1109/CVPR.2018.00765},
	author = {Alessandro Vianello and Jens Ackermann and Maximilian Diebold and Bernd J{\"a}hne}
}
@article {6314,
	title = {On the spectral bias of deep neural networks},
	journal = {arXiv preprint arXiv:1806.08734},
	year = {2018},
	author = {Rahaman, N and Arpit, D and Baratin, A and Draxler, F and Lin, M and Fred A. Hamprecht and Bengio, Y and Courville, A}
}
@proceedings {6267,
	title = {Trust your Model: Light Field Depth Estimation with inline Occlusion Handling},
	year = {2018},
	doi = {10.1109/CVPR.2018.00476},
	author = {Hendrik Schilling and Maximilian Diebold and Carsten Rother and Bernd J{\"a}hne}
}
@conference {Schilling2018,
	title = {Trust your Model: Light Field Depth Estimation with Inline Occlusion Handling},
	booktitle = {Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition},
	year = {2018},
	pages = {4530{\textendash}4538},
	abstract = {We address the problem of depth estimation from light-field images. Our main contribution is a new way to handle occlusions which improves general accuracy and quality of object borders. In contrast to all prior work we work with a model which directly incorporates both depth and occlusion, using a local optimization scheme based on the PatchMatch algorithm. The key benefit of this joint approach is that we utilize all available data, and not erroneously discard valuable information in pre-processing steps. We see the benefit of our approach not only at improved object boundaries, but also at smooth surface reconstruction, where we outperform even methods which focus on good surface regularization. We have evaluated our method on a public light-field dataset, where we achieve state-of-the-art results in nine out of twelve error metrics, with a close tie for the remaining three.},
	isbn = {9781538664209},
	issn = {10636919},
	doi = {10.1109/CVPR.2018.00476},
	author = {Schilling, Hendrik and Maximilian Diebold and Carsten Rother and Bernd J{\"a}hne}
}
@article {Vianello-etal-2017-TM,
	title = {3D reconstruction by a combined structure tensor and Hough transform light field approach},
	journal = {tm - Technisches Messen},
	year = {2017},
	abstract = {Disparity estimation using the structure tensor is a local approach to determine orientation in Epipolar Plane Images. A global extension would lead to more precise and robust estimations. In this work, a novel algorithm for 3D reconstruction from linear light fields is proposed. This method uses a modified version of the Progressive Probabilistic Hough Transform to extract orientations from Epipolar Plane Images, allowing to achieve high quality disparity maps. To this aim, the structure tensor estimates are used to speed up computation and improve the disparity estimation near occlusion boundaries. The new algorithm is evaluated on both synthetic and real light field datasets, and compared with classical local disparity estimation techniques based on the structure tensor.},
	doi = {10.1515/teme-2017-0010},
	author = {Alessandro Vianello and Giulio Manfredi and Maximilian Diebold and Bernd J{\"a}hne}
}
@conference {Dalitz2017,
	title = {Compressed Motion Sensing},
	booktitle = {Proc. SSVM},
	series = {LNCS},
	volume = {10302},
	year = {2017},
	publisher = {Springer},
	organization = {Springer},
	author = {Dalitz, R. and Petra, S. and Schn{\"o}rr, C.}
}
@proceedings {6204,
	title = {Cost-efficient Gradient Boosting},
	year = {2017},
	author = {Peter, S. and Ferran Diego and Fred A. Hamprecht and Nadler, B}
}
@article {schilling2017,
	title = {On the design of a fractal calibration pattern for improved camera calibration},
	journal = {tm - Technisches Messen},
	volume = {84},
	year = {2017},
	pages = {440{\textendash}451},
	doi = {10.1515/teme-2017-0013},
	author = {Hendrik Schilling and Maximilian Diebold and Marcel Gutsche and Bernd J{\"a}hne}
}
@techreport {Kruse,
	title = {Learning to Push the Limits of Efficient FFT-based Image Deconvolution - Supplemental Material},
	year = {2017},
	abstract = {1. Details about boundary adjustment comparison Section 4.3 of the main paper compares our proposed boundary adjustment (BA) strategy (Our BA, cf. Eq. 17 and Fig. 2 of the main paper) to the traditional edgetapering method (ET once, cf. Eq. 11 of the main paper) and the BA approach (ET each) of CSF [3]; these BA strategies are compared within our FDN model, the CSF model, and a standard Wiener filter [5]. Specifically, we use the publicly available code to train different variants of the CSF model on a dataset of the same size as ours, and only adjust the BA strategy. Furthermore, we apply the Wiener filter as defined in Eq. 2 of the main paper, which we can use iteratively with our BA approach by replacing y with ϕ t (y, k, x t); we estimate the expected image spectrum n from 3000 clean image patches. While our BA comparison is depicted visually in Fig. 5 of the main paper, Table 1 also provides the numeric results and additionally includes stages 6-10 of our FDN model. As compared to the BA approach of CSF (ET each), the results suggest that CSF would also benefit from further stages if used with our BA strategy (cf. 6 th column). Remarkably, the performance of the Wiener filter is not even fully saturated after 50 iterations (Wiener 50) when applied with our BA approach (cf. 3 rd column, only every 5 th step shown after iteration 10). Fig. 1 shows an example where our proposed BA strategy yields a substantial improvement in image quality compared to standard edgetapering (ET once).},
	author = {Kruse, Jakob and Carsten Rother and Schmidt, Uwe and Dresden, T U}
}
@proceedings {6201,
	title = {Locally Adaptive Probabilistic Models for Global Segmentation of Pathological OCT Scans},
	year = {2017},
	pages = {177-184},
	doi = {10.1007/978-3-319-66182-7_21},
	author = {Rathke, F and Desana, M and Schn{\"o}rr, C}
}
@conference {Rathke2017,
	title = {Locally Adaptive Probabilistic Models for Global Segmentation of Pathological OCT Scans},
	booktitle = {Proc. MICCAI},
	year = {2017},
	author = {Rathke, F. and Desana, M. and Schn{\"o}rr, C.}
}
@article {6210,
	title = {An Objective Comparison of Cell Tracking Algorithms},
	journal = {Nature Methods},
	volume = {14},
	year = {2017},
	pages = {1141-1152},
	doi = {10.1038/NMETH.447},
	author = {Ulman, V. and Ma{\v s}ka, M. and Magnusson, K .E. G. and Ronneberger, O. and Haubold, C. and Harder, N. and Matula, P. and Matula, P. and Svoboda, D. and Radojevic, M. and Smal, I. and Karl Rohr and Jald{\'e}n, J. and Blau, H. M. and Dzyubachyk, O. and Lelieveldt, B. and Xiao, P. and Li, Y. and Cho, S-Y. and Dufour, A. and Olivo-Marin, J. C. and Reyes-Aldasoro, C. C. and Solis-Lemus, J. A. and Bensch, R. and Brox, T. and Stegmaier, J. and Mikut, R. and Wolf, S. and Fred A. Hamprecht and Esteves, T. and Quelhas, P. and Demirel, {\"O}. and Malstr{\"o}m, L. and Jug, F. and Toman{\v c}{\'a}k, P. and Meijering, E. and Mu{\~n}oz-Barrutia, A. and Kozubek, M. and Ortiz-de-Solorzano, C.}
}
@conference {6193,
	title = {Self-supervised Learning of Pose Embeddings from Spatiotemporal Relations in Videos},
	booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},
	year = {2017},
	abstract = {Human pose analysis is presently dominated by deep convolutional networks trained with extensive manual annotations of joint locations and beyond. To avoid the need for expensive labeling, we exploit spatiotemporal relations in training videos for self-supervised learning of pose embeddings. The key idea is to combine temporal ordering and spatial placement estimation as auxiliary tasks for learning pose similarities in a Siamese convolutional network. Since the self-supervised sampling of both tasks from natural videos can result in ambiguous and incorrect training labels, our method employs a curriculum learning idea that starts training with the most reliable data samples and gradually increases the difficulty. To further refine the training process we mine repetitive poses in individual videos which provide reliable labels while removing inconsistencies. Our pose embeddings capture visual characteristics of human pose that can boost existing supervised representations in human pose estimation and retrieval. We report quantitative and qualitative results on these tasks in Olympic Sports, Leeds Pose Sports and MPII Human Pose datasets.},
	author = {{\"O}mer S{\"u}mer and Tobias Dencker and Bj{\"o}rn Ommer}
}
@proceedings {6205,
	title = {Sparse convolutional coding for neuronal assembly detection},
	year = {2017},
	author = {Peter, S. and Kirschbaum, E. and M. Both and Campbell, L. A. and Harvey, B. K. and Heins, C. and Durstewitz, D. and Ferran Diego and Fred A. Hamprecht}
}
@proceedings {schilling-etal-2016-ForumBildverarbeitung,
	title = {3D Reconstruction by a Combined Structure Tensor and Hough Transform Light-Field Approach},
	year = {2016},
	abstract = {Disparity estimation using the structure tensor is a local approach to determine orientation in Epipolar Plane Images. A global extension would lead to more precise and robust estimations. In this work, a novel algorithm for 3D reconstruction from linear light fields is porposed. It uses a modified Progressive Probabilistic Hough Transform, in combination with the structure tensor, to extract orientations from Epipolar Plane Images edge maps, allowing to achieve high quality disparity maps.},
	isbn = {978-3-7315-0587-7},
	doi = {10.5445/KSP/1000059899},
	url = {https://doi.org/10.5445/KSP/1000059899},
	author = {Alessandro Vianello and Giulio Manfredi and Maximilian Diebold and Bernd J{\"a}hne}
}
@booklet {Desana2016,
	title = {Expectation Maximization for Sum-Product Networks as Exponential Family Mixture Models},
	year = {2016},
	note = {ArXiv},
	month = {April},
	url = {http://arxiv.org/abs/1604.07243},
	author = {Desana, M. and Schn{\"o}rr, C.}
}
@proceedings {schilling-etal-2016-ForumBildverarbeitung,
	title = {A fractal calibration pattern for improved camera calibration},
	year = {2016},
	abstract = {Camera calibration, crucial for computer vision tasks, often relies on planar calibration targets to calibrate the camera parameters. This work explores a planar, fractal, self-identifying calibration pattern, which provides a high density of calibration points for a large range of magnification factors. An evaluation on ground truth data shows the target provides very high accuracy over a wide range of conditions.},
	doi = {10.5445/KSP/1000059899},
	url = {https://doi.org/10.5445/KSP/1000059899},
	author = {Hendrik Schilling and Maximilian Diebold and Marcel Gutsche and Hamza Aziz-Ahmad and Bernd J{\"a}hne}
}
@conference {DBLP:conf/cvpr/DieboldJG16,
	title = {Heterogeneous Light Fields},
	booktitle = {2016 {IEEE} Conference on Computer Vision and Pattern Recognition, {CVPR} 2016, Las Vegas, NV, USA, June 27-30, 2016},
	year = {2016},
	abstract = {In contrast to traditional binocular or multi-view stereo approaches, the adequately sampled space of observations in light-field imaging allows, to obtain dense and high quality depth maps. It also extends capabilities beyond those of traditional methods. Previously, constant intensity has been assumed for estimating disparity of orientation in most approaches to analyze epipolar plane images (EPIs). Here, we introduce a modified structure tensor approach which improves depth estimation. This extension also includes a model of non-constant intensity on EPI manifolds. We derive an approach to estimate high quality depth maps in luminance-gradient light fields, as well as in color-filtered light fields. Color-filtered light fields pose particular challenges due to the fact that structures can change significantly in appearance with wavelength and can completely vanish at some wavelength. We demonstrate solutions to this challenge and obtain a dense sRGB image reconstruction in addition to dense depth maps.},
	doi = {10.1109/CVPR.2016.193},
	url = {http://dx.doi.org/10.1109/CVPR.2016.193},
	author = {Maximilian Diebold and Alexander Gatto and Bernd J{\"a}hne}
}
@conference {Mund2016,
	title = {Introducing LiDAR Point Cloud-based Object Classification for Safer Apron Operations},
	booktitle = {International Symposium on Enhanced Solutions for Aircraft and Vehicle Surveillance Applications},
	year = {2016},
	abstract = {Current procedures for conventional and remote airport ground control still rely on the direct (camera-) view. Despite further support by different Radar applications occasional shortcomings in the awareness of the responsible controllers may occur, particularly under adverse weather conditions, giving rise to capacity backlogs, incidents and accidents. As Laser scanners and computer vision algorithms have reached new performance levels in recent years, we proposed a novel concept for complete and independent airport apron surveillance based on LiDAR 3D point data. In this paper we extend our object detection/segmentation technique by addressing object classification in LiDAR 3D scans. We hereby enable LiDAR{\textquoteleft}s unique capability to classify non-cooperative objects by means of a single sensor and learned model knowledge. Our technique was able to classify and to estimate the poses of an Airbus A319-100 and a Boeing B737-700 parked on the airport apron. In the future we will enhance our classification technique to a wider range of objects including moving ground vehicles and pedestrians.},
	keywords = {- lidar, 3d point cloud, aircraft, airport ground surveillance, apron control, apron control rely on, classification, current legacy procedures for, laser scanning, pose estimation},
	url = {https://goo.gl/28Yoqh},
	author = {Mund, Johannes and Michel, Frank and Dieke-Meier, Franziska and Fricke, Hartmut and Meyer, Lothar and Carsten Rother}
}
@proceedings {6081,
	title = {Learning Diverse Models: The Coulomb Structured Support Vector Machine},
	volume = {LNCS 9907},
	year = {2016},
	pages = {585-599},
	publisher = {Springer},
	doi = { 10.1007/978-3-319-46487-9_36},
	author = {Schiegg, M. and Ferran Diego and Fred A. Hamprecht}
}
@phdthesis {diebold2016,
	title = {Light-Field Imaging and Heterogeneous Light Fields},
	volume = {Dissertation},
	year = {2016},
	publisher = {IWR, Univ. Heidelberg},
	type = {phd},
	doi = {10.11588/heidok.00020560},
	author = {Maximilian Diebold}
}
@proceedings {6063,
	title = {Structured Regression Gradient Boosting},
	year = {2016},
	pages = {1459-1467},
	doi = { 10.1109/CVPR.2016.162},
	author = {Ferran Diego and Fred A. Hamprecht}
}
@proceedings {6079,
	title = {Variational weakly-supervised Gaussian processes},
	year = {2016},
	author = {Kandemir, M and Manuel Hau{\ss}mann and Ferran Diego and Rajamani, K and van der Laak, J and Fred A. Hamprecht}
}
@article {6033,
	title = {Virtual Raters for Reproducible and Objective Assessments in Radiology},
	journal = {Nature Scientific Reports},
	volume = {6},
	year = {2016},
	doi = {10.1038/srep25007},
	author = {Kleesiek, J. and Petersen, J. and D{\"o}ring, M. and Maier-Hein, K. and Ullrich K{\"o}the and Wick, W. and Fred A. Hamprecht and M. Bendszus and A. Biller}
}
@inbook {Krolla-etal-2015-LF4CV,
	title = {Light Field from Smartphone-Based Dual Video},
	booktitle = {Computer Vision - ECCV 2014 Workshops: Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part II},
	year = {2015},
	pages = {600{\textendash}610},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	isbn = {978-3-319-16181-5},
	doi = {10.1007/978-3-319-16181-5_46},
	url = {http://dx.doi.org/10.1007/978-3-319-16181-5_46},
	author = {Bernd Krolla and Maximilian Diebold and Didier Stricker}
}
@proceedings {diebold-etal-2015-SPIE,
	title = {Light-field camera design for high-accuracy depth estimation},
	year = {2015},
	month = {06/2015},
	abstract = {Light-field imaging is a research field with applicability in a variety of imaging areas including 3D cinema, entertainment, robotics, and any task requiring range estimation. In contrast to binocular or multi-view stereo approaches, capturing light fields means densely observing a target scene through a window of viewing directions. A principal benefit in light-field imaging for range computation is that one can eliminate the error-prone and computationally expensive process of establishing correspondence. The nearly continuous space of observation allows to compute highly accurate and dense depth maps free of matching. Here, we discuss how to structure the imaging system for optimal ranging over a defined volume - what we term a bounded frustum. We detail the process of designing the light-field setup, including practical issues such as camera footprint and component size influence the depth of field, lateral and range resolution. Both synthetic and real captured scenes are used to analyze the depth precision resulting from a design, and to show how unavoidable inaccuracies such as camera position and focal length variation limit depth precision. Finally, inaccuracies may be sufficiently well compensated through calibration and must be eliminated at the outset.},
	doi = {http://dx.doi.org/10.1117/12.2184845},
	author = {Maximilian Diebold and Oliver Blum and Marcel Gutsche and Sven Wanner and Christoph S. Garbe and Harlyn Baker and Bernd J{\"a}hne}
}
@conference {diebold2015,
	title = {Light-field camera design for high-accuracy depth estimation},
	booktitle = {Videometrics, Range Imaging, and Applications XIII},
	year = {2015},
	publisher = {SPIE},
	organization = {SPIE},
	doi = {10.1117/12.2184845},
	author = {M. Diebold and O. Blum and M. Gutsche and S. Wanner and C. Garbe and H. Baker and B. J{\"a}hne},
	editor = {Fabio Remondino and Mark R. Shortis}
}
@article {Didden2014,
	title = {Shape from Texture using Locally Scaled Point Processes},
	journal = {Image Anal. Stereol.},
	volume = {34},
	number = {3},
	year = {2015},
	pages = {161-170},
	author = {Didden, E.-M. and Thorarinsdottir, T.L. and Lenkoski, A. and Schn{\"o}rr, C.}
}
@mastersthesis {decker_automated,
	title = {Automated Animal Behavior Classification},
	year = {2014},
	school = {University of Heidelberg},
	author = {Decker, C.}
}
@conference {decker_14_detecting,
	title = {Detecting individual body parts improves mouse behavior classification},
	booktitle = {Workshop on visual observation and analysis of Vertebrate And Insect Behavior (VAIB), 22nd International Conference on Pattern Recognition (ICPR). Proceedings},
	year = {2014},
	note = {1},
	author = {Decker, C. and Fred A. Hamprecht}
}
@conference {Denitiu2014,
	title = {An Entropic Perturbation Approach to TV-Minimization for Limited-Data Tomography},
	booktitle = {Discrete Geometry for Computer Imagery (DGCI) 2014},
	year = {2014},
	pages = {262--274},
	publisher = {Springer},
	organization = {Springer},
	author = {Andreea Denitiu and Stefania Petra and Schn{\"o}rr, Claudius and Christoph Schn{\"o}rr},
	editor = {Elena Barcucci and Frosini, Andrea and Eds Rinaldi, Simone}
}
@conference {Denitiu2014,
	title = {An Entropic Perturbation Approach to TV-Minimization for Limited-Data Tomography},
	booktitle = {Discrete Geometry for Computer Imagery (DGCI) 2014},
	series = {LNCS},
	year = {2014},
	pages = {262{\textendash}274},
	publisher = {Springer},
	organization = {Springer},
	author = {Andreea Denitiu and Petra, Stefania and Schn{\"o}rr, Claudius and Christoph Schn{\"o}rr},
	editor = {Elena Barcucci and Frosini,Andrea and Eds Rinaldi,Simone}
}
@conference {Hoai2014,
	title = {Learning discriminative localization from weakly labeled data},
	booktitle = {Pattern Recognition},
	volume = {47},
	number = {3},
	year = {2014},
	month = {mar},
	pages = {1523{\textendash}1534},
	abstract = {Visual categorization problems, such as object classification or action recognition, are increasingly often approached using a detection strategy: a classifier function is first applied to candidate subwindows of the image or the video, and then the maximum classifier score is used for class decision. Traditionally, the subwindow classifiers are trained on a large collection of examples manually annotated with masks or bounding boxes. The reliance on time-consuming human labeling effectively limits the application of these methods to problems involving very few categories. Furthermore, the human selection of the masks introduces arbitrary biases (e.g., in terms of window size and location) which may be suboptimal for classification. We propose a novel method for learning a discriminative subwindow classifier from examples annotated with binary labels indicating the presence of an object or action of interest, but not its location. During training, our approach simultaneously localizes the instances of the positive class and learns a subwindow SVM to recognize them. We extend our method to classification of time series by presenting an algorithm that localizes the most discriminative set of temporal segments in the signal. We evaluate our approach on several datasets for object and action recognition and show that it achieves results similar and in many cases superior to those obtained with full supervision. {\textcopyright} 2013 Elsevier Ltd. All rights reserved.},
	keywords = {Discriminative discovery, Event detection, Image classification, Object detection, Time series classification, Weakly supervised learning},
	issn = {00313203},
	doi = {10.1016/j.patcog.2013.09.028},
	author = {Hoai, Minh and Torresani, Lorenzo and De La Torre, Fernando and Carsten Rother}
}
@article {Denitiu2014a,
	title = {Phase Transitions and Cosparse Tomographic Recovery of Compound Solid Bodies from Few Projections},
	journal = {Fundamenta Informaticae},
	volume = {135},
	year = {2014},
	pages = {73--102},
	author = {Andreea Denitiu and Stefania Petra and Schn{\"o}rr, Cl. and Christoph Schn{\"o}rr}
}
@article {Denitiu2014a,
	title = {Phase Transitions and Cosparse Tomographic Recovery of Compound Solid Bodies from Few Projections},
	journal = {Fundamenta Informaticae},
	volume = {135},
	year = {2014},
	pages = {73{\textendash}102},
	author = {Andreea Denitiu and Petra, S. and Schn{\"o}rr, Cl. and Christoph Schn{\"o}rr}
}
@article {Distributions2014,
	title = {Proof of Lemma 2 Proof of Lemma 3 Proof of Theorem 4 Proof of Lemma 10},
	journal = {Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics},
	number = {16},
	year = {2014},
	pages = {9{\textendash}11},
	abstract = {{Let us write down the linear program corresponding to the QPBO method. The roof duality relaxation for function E is given by equation (17). Adding pairwise terms Cx a x b for a, b ∈ A(p)},
	author = {Distributions, Laplace}
}
@conference {drory_14_semi-global,
	title = {Semi-Global Matching: A Principled Derivation in Terms of Message Passing},
	booktitle = {GCPR. Proceedings},
	number = {8753},
	year = {2014},
	note = {1},
	pages = {43-53},
	doi = {10.1007/978-3-319-11752-2_4},
	author = {Drory, A. and Haubold, C. and Avidan, S. and Fred A. Hamprecht}
}
@conference {diego_14_sparse,
	title = {Sparse Space-Time Deconvolution for Calcium Image Analysis},
	booktitle = {NIPS. Proceedings},
	year = {2014},
	note = {1},
	pages = {64-72},
	url = {http://papers.nips.cc/paper/5342-sparse-space-time-deconvolution-for-calcium-image-analysis},
	author = {Ferran Diego and Fred A. Hamprecht}
}
@conference {krolla-etall-2014-BMVC,
	title = {Spherical Light Fields},
	booktitle = {Proceedings of the British Machine Vision Conference},
	year = {2014},
	publisher = {BMVA Press},
	organization = {BMVA Press},
	abstract = {A full view spherical camera exploits its extended field of view to map the complete environment onto a 2D image plane. Thus, with a single shot, it delivers a lot more information about the surroundings than one can gather with a normal perspective or plenoptic camera, which are commonly used in light field imaging. However, in contrast to a light field camera, a spherical camera does not capture directional information about the incident light, and thus a single shot from a spherical camera is not sufficient to reconstruct 3D scene geometry. In this paper, we introduce a method combining spherical imaging with the light field approach. To obtain 3D information with a spherical camera, we capture several independent spherical images by applying a constant vertical offset between the camera positions and combine the images in a Spherical Light Field (SLF). We can then compute disparity maps by structure tensor orientation analysis on epipolar plane images, which in this context are 2D cuts through the spherical light field with constant azimuth angle. This method competes with the acquisition range of laser scanners and allows for a fast and extensive recording of a given scene. We benchmark our approach by comparing disparity maps of ray-traced scenes against its ground truth. Further we provide disparity maps of real world datasets. },
	author = {Bernd Krolla and Maximilian Diebold and Bastian Goldl{\"u}cke and Didier Stricker}
}
@conference {fiaschi_14_tracking,
	title = {Tracking indistinguishable translucent objects over time using weakly supervised structured learning},
	booktitle = {CVPR. Proceedings},
	year = {2014},
	note = {1},
	pages = {2736 - 2743},
	doi = {10.1109/CVPR.2014.356},
	author = {Fiaschi, L. and Ferran Diego and Karl-Heinz Grosser and Schiegg, M. and Ullrich K{\"o}the and Zlatic, M. and Fred A. Hamprecht}
}
@article {diego_13_automated,
	title = {Automated Identification of Neuronal Activity from Calcium Imaging by Sparse Dictionary Learning},
	journal = {ISBI 2013. Proceedings},
	number = {0236},
	year = {2013},
	note = {1},
	pages = {1058-1061},
	doi = {10.1109/ISBI.2013.6556660},
	author = {Ferran Diego and Reichinnek, S. and M. Both and Fred A. Hamprecht}
}
@article {mikut_13_automated,
	title = {Automated Processing of Zebrafish Imaging Data: A Survey},
	journal = {Zebrafish},
	volume = {10 (3)},
	year = {2013},
	doi = {10.1089/zeb.2013.0886},
	author = {Mikut, R. and Dickmeis, T. and Driever, W. and Geurts, P. and Fred A. Hamprecht and Bernhard X. Kausler and Ledesma-Carbayo, M. and Marée, R. and Mikula, K. and Pantazis, P. and Ronneberger, O. and Santos, A. and Stotzka, R.}
}
@conference {diebold-etal-2013-VMV,
	title = {Epipolar Plane Image Refocusing for Improved Depth Estimation and Occlusion Handling.},
	booktitle = {VMV},
	year = {2013},
	publisher = {Eurographics Association},
	organization = {Eurographics Association},
	abstract = {In contrast to traditional imaging, the higher dimensionality of a light field offers directional information about the
captured intensity. This information can be leveraged to estimate the disparity of 3D points in the captured scene.
A recent approach to estimate disparities analyzes the structure tensor and evaluates the orientation on epipolar
plane images (EPIs). While the resulting disparity maps are generally satisfying, the allowed disparity range is
small and occlusion boundaries can become smeared and noisy. In this paper, we first introduce an approach to
extend the total allowed disparity range. This allows for example the investigation of camera setups with a larger
baseline, like in the Middlebury 3D light fields. Second, we introduce a method to handle the difficulties arising at
boundaries between fore- and background objects to achieve sharper edge transitions.},
	keywords = {dblp},
	isbn = {978-3-905674-51-4},
	url = {http://dblp.uni-trier.de/db/conf/vmv/vmv2013.html$\#$DieboldG13},
	author = {Maximilian Diebold and Bastian Goldl{\"u}cke}
}
@article {donath_13_how,
	title = {How Good is Crowdsourcing for Optical Flow Ground Truth Generation?},
	journal = {submitted to CVPR},
	year = {2013},
	note = {1},
	author = {Donath, A. and Daniel Kondermann}
}
@conference {diego_13_learning2,
	title = {Learning Multi-Level Sparse Representation},
	booktitle = {NIPS. Proceedings},
	year = {2013},
	note = {1},
	url = {http://papers.nips.cc/paper/5076-learning-multi-level-sparse-representations},
	author = {Ferran Diego and Fred A. Hamprecht}
}
@conference {diego_13_learning,
	title = {Learning Multi-Level Sparse Representation for Identifying Neuronal Activity},
	booktitle = {Signal Processing with Adaptive Sparse Structured Representations Workshop (SPARS). Book of Abstracts.},
	year = {2013},
	note = {1},
	author = {Ferran Diego and Fred A. Hamprecht}
}
@conference {kroeger_13_learning,
	title = {Learning to Segment Neurons with Non-local Quality Measures},
	booktitle = {MICCAI 2013. Proceedings, part II},
	volume = {8150},
	year = {2013},
	note = {1},
	pages = {419-427},
	publisher = {Springer},
	organization = {Springer},
	doi = {10.1007/978-3-642-40763-5_52},
	author = {Thorben Kr{\"o}ger and Mikula, S. and Denk, W. and Ullrich K{\"o}the and Fred A. Hamprecht}
}
@article {davis2013,
	title = {Time-of-Flight Imaging: Algorithms, Sensors and Applications (Dagstuhl Seminar 12431)},
	journal = {Dagstuhl Reports},
	volume = {2},
	number = {10},
	year = {2013},
	pages = {79--104},
	publisher = {Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
	abstract = {This report documents the program and the outcomes of Dagstuhl Seminar 12431 "Time-of-Flight Imaging: Algorithms, Sensors and Applications". The seminar brought together researchers with diverse background from both academia and industry to discuss various aspects of Time-of-Flight imaging and general depth sensors. The executive summary and abstracts of the talks given during the seminar as well as the outcome of several working groups on specific research topics are presented in this report.},
	issn = {2192-5283},
	doi = {http://dx.doi.org/10.4230/DagRep.2.10.79},
	url = {http://drops.dagstuhl.de/opus/volltexte/2013/3904},
	editor = {Davis, James and Bernd J{\"a}hne and Andreas Kolb and Raskar, Ramesh and Theobalt, Christian and Davis, James and Bernd J{\"a}hne and Raskar, Ramesh and Theobalt, Christian and Andreas Kolb}
}
@article {andres_11_3d,
	title = {3D Segmentation of SBFSEM Images of Neuropil by a Graphical Model over Supervoxel Boundaries},
	journal = {Medical Image Analysis},
	volume = {16 (2012)},
	year = {2012},
	note = {1},
	pages = {796-805},
	doi = {10.1016/j.media.2011.11.004},
	author = {Bj{\"o}rn Andres and Ullrich K{\"o}the and Thorben Kr{\"o}ger and Helmstaedter, M. and K. L. Briggmann and Denk, W. and Fred A. Hamprecht}
}
@article {zechmann_12_automated,
	title = {Automated vs. manual pattern recognition of 3D 1H MRSI data of patients with prostate cancer},
	journal = {Academic Radiology},
	volume = {19, 6},
	year = {2012},
	pages = {675-684},
	doi = {10.1016/j.acra.2012.02.014},
	author = {C. M. Zechmann and Bjoern H. Menze and B. Michael Kelm and Zamecnik, P. and Ikinger, U. and Waldherr, R. and Delorme, S. and Fred A. Hamprecht and Bachert, P.}
}
@conference {andres_12_globally,
	title = {Globally Optimal Closed-Surface Segmentation for Connectomics},
	booktitle = {ECCV 2012. Proceedings, Part 3},
	number = {7574},
	year = {2012},
	note = {1},
	pages = {778-791},
	doi = {10.1007/978-3-642-33712-3_56},
	author = {Bj{\"o}rn Andres and Thorben Kr{\"o}ger and K. L. Briggmann and Denk, W. and Norogod, N. and G. W. Knott and Ullrich K{\"o}the and Fred A. Hamprecht}
}
@article {diego_12_joint,
	title = {Joint SpatioTemporal Alignment of Sequences},
	journal = {IEEE Transactions on Multimedia (TMM)},
	volume = {PP (99)},
	year = {2012},
	note = {1},
	pages = {1},
	doi = {10.1109/TMM.2013.2247390},
	author = {Ferran Diego and Serrat, J. and López, A. M.}
}
@article {alvarez_12_road,
	title = {Road Geometry Classification by Adaptive Shape Models},
	journal = {IEEE Transactions on Intelligent Transportation Systems (ITS)},
	volume = {99},
	year = {2012},
	pages = {1-10},
	doi = {10.1109/TITS.2012.2221088},
	author = {Álvarez, J. M. and Gevers, T. and Ferran Diego and López, A. M.}
}
@conference {straehle_12_seeded,
	title = {Seeded watershed cut uncertainty estimators for guided interactive segmentation},
	booktitle = {CVPR 2012. Proceedings},
	year = {2012},
	note = {1},
	pages = {765 - 772},
	doi = {10.1109/CVPR.2012.6247747},
	author = {Christoph N. Straehle and Ullrich K{\"o}the and Briggman, K. and Denk, W. and Fred A. Hamprecht}
}
@conference {maier-hein2011,
	title = {Towards mobile augmented reality for on-patient visualization of medical images},
	booktitle = {Bildverarbeitung f{\"u}r die Medizin (2011)},
	year = {2011},
	pages = {389--393},
	publisher = {Springer},
	organization = {Springer},
	abstract = {Despite considerable technical and algorithmic developments related to the fields of medical image acquisition and processing in the past decade, the devices used for visualization of medical images have undergone rather minor changes. As anatomical information is typically shown on monitors provided by a radiological work station, the physician has to mentally transfer internal structures shown on the screen to the patient. In this work, we present a new approach to on-patient visualization of 3D medical images, which combines the concept of augmented reality (AR) with an intuitive interaction scheme. The method requires mounting a Time-of-Flight (ToF) camera to a portable display (e.g., a tablet PC). During the visualization process, the pose of the camera and thus the viewing direction of the user is continuously determined with a surface matching algorithm. By moving the device along the body of the patient, the physician gets the impression of being able to look directly into the human body. The concept can be used for intervention planning, anatomy teaching and various other applications that require intuitive visualization of 3D data.},
	doi = {10.1007/978-3-642-19335-4_80},
	author = {Lena Maier-Hein and A. M. Franz and M. Fangerau and Schmidt, Mirko and Alexander Seitel and Sven Mersmann and T. Kilgus and A. Groch and K. Yung and Thiago R. dos Santos and Hans-Peter Meinzer},
	editor = {H. Handels and J. Ehrhardt and Hans-Peter Meinzer and T. Tolxdorff and T. M. Deserno}
}
@conference {Lellmann2010a,
	title = {Fast and Exact Primal-Dual Iterations for Variational Problems in Computer Vision},
	booktitle = {European Conference on Computer Vision (ECCV)},
	volume = {6312},
	year = {2010},
	pages = {494--505},
	publisher = {Springer Berlin / Heidelberg},
	organization = {Springer Berlin / Heidelberg},
	author = {Lellmann, J. and Breitenreicher, D. and Christoph Schn{\"o}rr},
	editor = {Daniilidis, K. and Maragos, P. and Paragios, N.}
}
@conference {Lellmann2010a,
	title = {Fast and Exact Primal-Dual Iterations for Variational Problems in Computer Vision},
	booktitle = {European Conference on Computer Vision (ECCV)},
	series = {LNCS},
	volume = {6312},
	year = {2010},
	pages = {494{\textendash}505},
	publisher = {Springer Berlin / Heidelberg},
	organization = {Springer Berlin / Heidelberg},
	author = {Lellmann, J. and Breitenreicher, D. and Schn{\"o}rr, C.},
	editor = {Daniilidis, K. and Maragos, P. and Paragios, N.}
}
@mastersthesis {daume2010,
	title = {Fusion von Midwave-infrared- und Longwave-infrared-W{\"a}rmebildger{\"a}ten zur Klassifizierung von Flugobjekten},
	year = {2010},
	school = {Institut f{\"u}r Umweltphysik, Fakult{\"a}t f{\"u}r Physik und Astronomie, Univ.\ Heidelberg},
	author = {Dominik Daume}
}
@article {Ding2010,
	title = {Interactive image segmentation using probabilistic hypergraphs},
	journal = {Pattern Recognition},
	volume = {43},
	number = {5},
	year = {2010},
	pages = {1863{\textendash}1873},
	abstract = {This paper introduces a novel interactive framework for segmenting images using probabilistic hypergraphs which model the spatial and appearance relations among image pixels. The probabilistic hypergraph provides us a means to pose image segmentation as a machine learning problem. In particular, we assume that a small set of pixels, which are referred to as seed pixels, are labeled as the object and background. The seed pixels are used to estimate the labels of the unlabeled pixels by learning on a hypergraph via minimizing a quadratic smoothness term formed by a hypergraph Laplacian matrix subject to the known label constraints. We derive a natural probabilistic interpretation of this smoothness term, and provide a detailed discussion on the relation of our method to other hypergraph and graph based learning methods. We also present a front-to-end image segmentation system based on the proposed method, which is shown to achieve promising quantitative and qualitative results on the commonly used GrabCut dataset. {\textcopyright} 2009 Elsevier Ltd. All rights reserved.},
	keywords = {Hypergraphs, Image segmentation, Interactive segmentation, Semi-supervised learning},
	issn = {00313203},
	doi = {10.1016/j.patcog.2009.11.025},
	url = {http://www.research.microsoft.com/vision/cambridge},
	author = {Ding, Lei and Yilmaz, Alper}
}
@conference {kappes_10_mrf,
	title = {MRF Inference by k-Fan Decomposition and Tight Lagrangian Relaxation},
	booktitle = {European Conference on Computer Vision (ECCV)},
	volume = {6313},
	year = {2010},
	note = {1},
	pages = {735--747},
	publisher = {Springer},
	organization = {Springer},
	doi = {10.1007/978-3-642-15558-1_53},
	author = {J{\"o}rg H. Kappes and Schmidt, S. and Christoph Schn{\"o}rr},
	editor = {Daniilidis, K. and Maragos, P. and Paragios, N.}
}
@conference {Kappes-ECCV2010,
	title = {MRF Inference by k-Fan Decomposition and Tight Lagrangian Relaxation},
	booktitle = {European Conference on Computer Vision (ECCV)},
	volume = {6313},
	year = {2010},
	pages = {735--747},
	publisher = {Springer Berlin / Heidelberg},
	organization = {Springer Berlin / Heidelberg},
	author = {J{\"o}rg H. Kappes and Schmidt, S. and Christoph Schn{\"o}rr},
	editor = {Daniilidis, K. and Maragos, P. and Paragios, N.}
}
@conference {Kappes-ECCV2010,
	title = {MRF Inference by k-Fan Decomposition and Tight Lagrangian Relaxation},
	booktitle = {European Conference on Computer Vision (ECCV)},
	volume = {6313},
	year = {2010},
	pages = {735{\textendash}747},
	publisher = {Springer Berlin / Heidelberg},
	organization = {Springer Berlin / Heidelberg},
	author = {Kappes, J. H. and Schmidt, S. and Schn{\"o}rr, C.},
	editor = {Daniilidis, K. and Maragos, P. and Paragios, N.}
}
@conference {kaster_10_object-oriented,
	title = {An object-oriented library for systematic training and comparison of classifiers for computer-assisted tumor diagnosis from MRSI measurements},
	booktitle = {Bildverarbeitung f{\"u}r die Medizin 2010 -- Algorithmen, Systeme, Anwendungen},
	year = {2010},
	note = {1},
	pages = {97-101},
	publisher = {Springer},
	organization = {Springer},
	author = {F. O. Kaster and Kassemeyer, S. and Merkel, B. and Nix, O. and Fred A. Hamprecht},
	editor = {T. M. Deserno and H. Handels and T. Tolxdorff and Hans-Peter Meinzer}
}
@conference {jaehne2010a,
	title = {Wind/wave-tunnel measurements of chemical enhancement of the carbon dioxide gas exchange rate},
	booktitle = {6th Int. Symp. Gas Transfer at Water Surfaces, Kyoto, May 17--21, 2010},
	year = {2010},
	note = {abstract},
	doi = {10.5281/zenodo.14928},
	author = {Bernd J{\"a}hne and Kai Degreif and Joachim Kuss}
}
@incollection {beushausen2009,
	title = {2D-measurement technique for simultaneous quantitative determination of mixing ratio and velocity field in microfluidic applications},
	volume = {106},
	year = {2009},
	pages = {155--164},
	publisher = {Springer},
	abstract = {Two-dimensional Molecular-Tagging-Velocimetry (2D-MTV) has been used to investigate velocity fields of liquid flow in a micro mixer. Optical tagging was realized by using caged dye. For the first time patterns were generated by structured laser illumination using optical masks. This allows the generation of nearly any imaginable pattern. The flow induced deformation of the optically written pattern is tracked by imaging of laser induced fluorescence. Quantitative analysis of raw image series is carried out by novel optical flow based techniques. A comparison to the standard technique of uPIV has also been conducted. Additionally Planar Spontaneous Raman Scattering (PSRS) was applied in order to determine concentration fields for mixtures of ethanol and water.},
	doi = {10.1007/978-3-642-01106-1_16},
	author = {Volker Beushausen and Karsten Roetmann and Waldemar Schmunk and Mike Wellhausen and Christoph S. Garbe and Bernd J{\"a}hne},
	editor = {W. Nitsche and C. Dobriloff}
}
@incollection {Petra-et-al-09a,
	title = {3D Tomography from Few Projections in Experimental Fluid Mechanics},
	volume = {106},
	year = {2009},
	pages = {63-72},
	publisher = {Springer},
	author = {Stefania Petra and Schr{\"o}der, A. and Christoph Schn{\"o}rr},
	editor = {W. Nitsche and C. Dobriloff}
}
@conference {hoernlein2009,
	title = {Boosting shift-invariant features},
	booktitle = {Pattern Recognition},
	volume = {5748},
	year = {2009},
	pages = {121--130},
	publisher = {Springer},
	organization = {Springer},
	abstract = {This work presents a novel method for training shift-invariant features using a Boosting framework. Features performing local convolutions followed by subsampling are used to achieve shift-invariance. Other systems using this type of features, e.g. Convolutional Neural Networks, use complex feed-forward networks with multiple layers. In contrast, the proposed system adds features one at a time using smoothing spline base classifiers. Feature training optimizes base classifier costs. Boosting sample-reweighting ensures features to be both descriptive and independent. Our system has a lower number of design parameters as comparable systems, so adapting the system to new problems is simple. Also, the stage-wise training makes it very scalable. Experimental results show the competitiveness of our approach.},
	doi = {10.1007/978-3-642-03798-6_13},
	author = {Thomas H{\"o}rnlein and Bernd J{\"a}hne and Herbert S{\"u}{\ss}e},
	editor = {Joachim Denzler and Gunther Notni}
}
@conference {kaster_09_classification,
	title = {Classification of Spectroscopic Images in the DIROlab Environment},
	booktitle = {World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany},
	volume = {25/V},
	number = {25050252},
	year = {2009},
	pages = {252--255},
	publisher = {Springer},
	organization = {Springer},
	doi = {10.1007/978-3-642-03904-1_70},
	author = {F. O. Kaster and B. Michael Kelm and C. M. Zechmann and M.-A. Weber and Fred A. Hamprecht and Nix, O.},
	editor = {D{\"o}ssel, Olaf and Schlegel, Wolfgang C.}
}
@conference {keraenen:2009,
	title = {Computational Analysis of Quantitative Changes in Gene Expression and Embryo Morphology between Species},
	booktitle = {Evolution-The Molecular Landscape},
	year = {2009},
	author = {Ker{\"a}nen, S. V. E. and DePace, A. and Luengo Hendriks, C. L. and Fowlkes, C. and Arbelaez, P. and Bj{\"o}rn Ommer and Brox, T. and Henriquez, C. and Wunderlich, Z. and Eckenrode, K. and B. Fischer and Hammonds, A. and Celniker, S. E.}
}
@incollection {garbe2009,
	title = {Spatiotemporal image analysis for flow measurements},
	volume = {106},
	year = {2009},
	pages = {289--305},
	publisher = {Springer},
	abstract = {In this chapter, a framework will be presented for measuring and modeling transport processes using novel visualization techniques and extended optical flow techniques for digital image sequence analysis. In this way, parameters besides the 2-D xy velocity components can be extracted concurrently from the acquired 2-D image sequences, such as wall shear rates and momentum transport close to boundaries, diffusion coefficients, and depth z in addition to the z velocity components. Depending on the application, particularly the temporal regularization can be enhanced, leading to stabilization of results and reduction of spatial regularization. This is frequently of high importance for flows close to boundaries. Results from applications will be presented from the fields of environmental and life sciences as well as from engineering.},
	doi = {10.1007/978-3-642-01106-1_29},
	author = {Christoph S. Garbe and Daniel Kondermann and Markus Jehle and Bernd J{\"a}hne},
	editor = {W. Nitsche and C. Dobriloff}
}
@incollection {Vlasenko-Schnoerr-09a,
	title = {Variational Approaches for Model-Based PIV and Visual Fluid Analysis},
	volume = {106},
	year = {2009},
	pages = {247-256},
	publisher = {Springer},
	author = {Vlasenko, A. and Christoph Schn{\"o}rr},
	editor = {W. Nitsche and C. Dobriloff}
}
@incollection {Vlasenko-Schnoerr-09a,
	title = {Variational Approaches for Model-Based PIV and Visual Fluid Analysis},
	volume = {106},
	year = {2009},
	pages = {247-256},
	publisher = {Springer},
	author = {Vlasenko, A. and Schn{\"o}rr, C.},
	editor = {Nitsche, W. and C. Dobriloff}
}
@incollection {berthe2009,
	title = {The wall PIV measurement technique for near wall flow fields in biofliud mechanics},
	volume = {106},
	year = {2009},
	pages = {11--20},
	publisher = {Springer},
	abstract = {This chapter describes the development of a new time resolved 3D PIV technique for near wall flow field measurements. This measurement technique, called wall-PIV, is based on Beer-Lambert{\textquoteright}s law. It substitutes the classical PIV laser sheet by a diffuse, monochromatic full-field illumination that is limited to the near wall region by an absorbing molecular dye in the fluid. Aimed range of applications is the investigation of flow fields next to one- or two dimensionally curved, possibly flexing surfaces. The three dimensional three component flow estimation uses a new optical flow algorithm, based on particle trajectories. Results of the measurement technique{\textquoteright}s application on a displacement pediatric blood pump are presented.},
	doi = {10.1007/978-3-642-01106-1_2},
	author = {A. Berthe and Daniel Kondermann and Bernd J{\"a}hne and U. Ketzscher},
	editor = {W. Nitsche and C. Dobriloff}
}
@conference {Nguyen2009,
	title = {Weakly supervised discriminative localization and classification: A joint learning process},
	booktitle = {Proceedings of the IEEE International Conference on Computer Vision},
	year = {2009},
	pages = {1925{\textendash}1932},
	abstract = {Visual categorization problems, such as object classification or action recognition, are increasingly often approached using a detection strategy: a classifier function is first applied to candidate subwindows of the image or the video, and then the maximum classifier score is used for class decision. Traditionally, the subwindow classifiers are trained on a large collection of examples manually annotated with masks or bounding boxes. The reliance on time-consuming human labeling effectively limits the application of these methods to problems involving very few categories. Furthermore, the human selection of the masks introduces arbitrary biases (e.g. in terms of window size and location) which may be suboptimal for classification. In this paper we propose a novel method for learning a discriminative subwindow classifier from examples annotated with binary labels indicating the presence of an object or action of interest, but not its location. During training, our approach simultaneously localizes the instances of the positive class and learns a subwindow SVM to recognize them. We extend our method to classification of time series by presenting an algorithm that localizes the most discriminative set of temporal segments in the signal. We evaluate our approach on several datasets for object and action recognition and show that it achieves results similar and in many cases superior to those obtained with full supervision. {\textcopyright}2009 IEEE.},
	isbn = {9781424444205},
	doi = {10.1109/ICCV.2009.5459426},
	author = {Nguyen, Minh Hoai and Torresani, Lorenzo and De La Torre, Fernando and Carsten Rother}
}
@conference {Nguyen2009a,
	title = {Weakly supervised discriminative localization and classification: A joint learning process},
	booktitle = {Proceedings of the IEEE International Conference on Computer Vision},
	year = {2009},
	pages = {1925{\textendash}1932},
	abstract = {Visual categorization problems, such as object classification or action recognition, are increasingly often approached using a detection strategy: a classifier function is first applied to candidate subwindows of the image or the video, and then the maximum classifier score is used for class decision. Traditionally, the subwindow classifiers are trained on a large collection of examples manually annotated with masks or bounding boxes. The reliance on time-consuming human labeling effectively limits the application of these methods to problems involving very few categories. Furthermore, the human selection of the masks introduces arbitrary biases (e.g. in terms of window size and location) which may be suboptimal for classification. In this paper we propose a novel method for learning a discriminative subwindow classifier from examples annotated with binary labels indicating the presence of an object or action of interest, but not its location. During training, our approach simultaneously localizes the instances of the positive class and learns a subwindow SVM to recognize them. We extend our method to classification of time series by presenting an algorithm that localizes the most discriminative set of temporal segments in the signal. We evaluate our approach on several datasets for object and action recognition and show that it achieves results similar and in many cases superior to those obtained with full supervision. {\textcopyright}2009 IEEE.},
	isbn = {9781424444205},
	doi = {10.1109/ICCV.2009.5459426},
	author = {Nguyen, Minh Hoai and Torresani, Lorenzo and De La Torre, Fernando and Carsten Rother}
}
@incollection {acker2008,
	title = {Inverse Problems and Parameter Identification in Image Processing},
	year = {2008},
	pages = {111--151},
	publisher = {Springer},
	abstract = {Many problems in imaging are actually inverse problems. One reason for this is that conditions and parameters of the physical processes underlying the actual image acquisition are usually not known. Examples for this are the inhomogeneities of the magnetic field in magnetic resonance imaging (MRI) leading to nonlinear deformations of the anatomic structures in the recorded images, material parameters in geological structures as unknown parameters for the simulation of seismic wave propagation with sparse measurement on the surface, or temporal changes in movie sequences given by intensity changes or moving image edges and resulting from deformation, growth and transport processes with unknown fluxes. The underlying physics is mathematically described in terms of variational problems or evolution processes. Hence, solutions of the forward problem are naturally described by partial differential equations. These forward models are reflected by the corresponding inverse problems as well. Beyond these concrete, direct modeling links to continuum mechanics abstract concepts from physical modeling are successfully picked up to solve general perceptual problems in imaging. Examples are visually intuitive methods to blend between images showing multiscale structures at different resolution or methods for the analysis of flow fields.},
	doi = {10.1007/978-3-540-75632-3_4},
	author = {Jens F. Acker and Benjamin Berkels and Kristian Bredies and Mamadou S. Diallo and Marc Droske and Christoph S. Garbe and Matthias Holschneider and Jaroslav Hron and Claudia Kondermann and Michail Kulesh and Peter Maass and Nadine Olischl{\"a}ger and Heinz-Otto Peitgen},
	editor = {R. Dahlhaus and J. Kurths and Timmer, J. and Peter Maass}
}
@incollection {garbe_08_nonlinear,
	title = {Nonlinear Analysis of Multi-Dimensional Signals},
	year = {2008},
	note = {1},
	pages = {231-288},
	publisher = {Springer},
	doi = {10.1007/978-3-540-75632-3_7},
	author = {Christoph S. Garbe and Kai Krajsek and Pavel Pavlov and Bj{\"o}rn Andres and Matthias M{\"u}hlich and Ingo Stuke and Cicero Mota and Martin B{\"o}hme and Martin Haker and Schuchert, T. and Hanno Scharr and Til Aach and Erhardt Barth},
	editor = {R. Dahlhaus and J. Kurths and Timmer, J. and Peter Maass}
}
@incollection {garbe2008,
	title = {Nonlinear analysis of multi-dimensional signals: local adaptive estimation of complex motion and orientation patterns},
	year = {2008},
	pages = {231-288},
	publisher = {Springer},
	abstract = {We consider the general task of accurately detecting and quantifying orientations in n-dimensional signals s. The main emphasis will be placed on the estimation of motion, which can be thought of as orientation in spatiotemporal signals. Associated problems such as the optimization of matched kernels for deriving isotropic and highly accurate gradients from the signals, optimal integration of local models, and local model selection will also be addressed.},
	doi = {10.1007/978-3-540-75632-3_7},
	author = {Christoph S. Garbe and Kai Krajsek and Pavel Pavlov and Bj{\"o}rn Andres and Matthias M{\"u}hlich and Ingo Stuke and Cicero Mota and Martin B{\"o}hme and Martin Haker and Tobias Schucher and Hanno Scharr and Til Aach and Erhardt Barth},
	editor = {R. Dahlhaus and J. Kurths and Timmer, J. and Peter Maass}
}
@conference {andres_08_segmentation,
	title = {Segmentation of SBFSEM Volume Data of Neural Tissue by Hierarchical Classification},
	booktitle = {Pattern Recognition. 30th DAGM Symposium Munich, Germany, June 10-13, 2008. Proceedings},
	volume = {5096},
	year = {2008},
	note = {1},
	pages = {142-152},
	publisher = {Springer},
	organization = {Springer},
	doi = {10.1007/978-3-540-69321-5_15},
	author = {Bj{\"o}rn Andres and Ullrich K{\"o}the and Helmstaedter, M. and Denk, W. and Fred A. Hamprecht},
	editor = {Gerhard Rigoll}
}
@article {weber_07_comparison,
	title = {Comparison of correctness of manuel and automatic evaluation of MR-spectrum with prostrate cancer},
	journal = {Der Urologe},
	volume = {46},
	number = {9},
	year = {2007},
	pages = {1252},
	doi = {10.1007/s00120-007-1488-1},
	author = {C. Weber and C. M. Zechmann and B. Michael Kelm and Zamecnik, R. and Hendricks, D. and Waldherr, R. and Fred A. Hamprecht and Delorme, S. and Bachert, P. and Ikinger, U.}
}
@incollection {garbe2007c,
	title = {Estimating the viscous shear stress at the water surface from active thermography},
	year = {2007},
	pages = {223--239},
	publisher = {Springer-Verlag},
	abstract = {A novel technique is presented that makes it possible to measure the viscous shear stress from active thermography. With a CO2 laser, patterns are written to the sea surface. This temperature structure is distorted by the linear velocity profile in the viscous boundary layer. Due to the non-zero penetration depth of both the laser and the infrared camera, this vertical velocity profile can be resolved. By resolving the velocity profile, the viscous shear stress can be extracted from the recorded image sequences. At the same time, the flow field at the water surface can be measured accurately. Estimating both quantities is only possible by modeling the imaging process as well as the velocity profile in the boundary layer. The model parameters can then be computed in a standard parameter estimation framework. This novel technique was tested both on simulated data and on measurements conducted in a small annular wind-wave flume. The friction velocity computed in this fashion compared favorably to independent measurements. Although not tested yet, this technique should be equally applicable to field measurements.},
	doi = {10.1007/978-3-540-36906-6_16},
	author = {Kai Degreif and Bernd J{\"a}hne and Bernd J{\"a}hne},
	editor = {Christoph S. Garbe and Christoph S. Garbe and Handler, R. A.}
}
@conference {menze_07_from,
	title = {From eigenspots to fisherspots -- latent spaces in the nonlinear detection of spot patterns in a highly variable background},
	booktitle = {Advances in data analysis},
	volume = {33},
	year = {2007},
	note = {1},
	pages = {255-262},
	publisher = {Springer},
	organization = {Springer},
	doi = {10.1007/978-3-540-70981-7_29},
	author = {Bjoern H. Menze and B. Michael Kelm and Fred A. Hamprecht},
	editor = {Lenz, H.-J. and Decker, R.}
}
@article {preusser2007,
	title = {A phase field method for joint denoising, edge detection, and motion estimation in image sequence processing.},
	journal = {SIAM Journal of Applied Mathematics},
	volume = {68},
	year = {2007},
	pages = {599-618},
	abstract = {The estimation of optical flow fields from image sequences is incorporated in a Mumford/Shah approach for image denoising and edge detection. Possibly noisy image sequences are considered as input and a piecewise smooth image intensity, a piecewise smooth motion field, and a joint discontinuity set are obtained as minimizers of the functional. The method simultaneously detects image edges and motion field discontinuities in a rigorous and robust way. It is able to handle information on motion that is concentrated on edges. Inherent to it is a natural multiscale approximation that is closely related to the phase field approximation for edge detection by Ambrosio and Tortorelli. We present an implementation for two-dimensional image sequences with finite elements in space and time. This leads to three linear systems of equations, which have to be solved in a suitable iterative minimization procedure. Numerical results and different applications underline the robustness of the approach presented.},
	doi = {10.1137/060677409},
	author = {Preusser, T. and Marc Droske and Christoph S. Garbe and Martin Rumpf and Alexandru Telea}
}
@conference {Schmidt-et-al-07,
	title = {Spine Detection and Labeling Using a Parts-Based Graphical Model},
	booktitle = {Proc. 20th International Conference on Information Processing in Medical Imaging (IPMI 2007)},
	volume = {4584},
	year = {2007},
	pages = {122-133},
	publisher = {Springer},
	organization = {Springer},
	author = {Schmidt, S. and J{\"o}rg H. Kappes and Bergtholdt, M. and Pekar, V. and Dries, S. and Bystrov, D. and Christoph Schn{\"o}rr}
}
@conference {Schmidt-et-al-07,
	title = {Spine Detection and Labeling Using a Parts-Based Graphical Model},
	booktitle = {Proc. 20th International Conference on Information Processing in Medical Imaging (IPMI 2007)},
	series = {LCNS},
	volume = {4584},
	year = {2007},
	pages = {122-133},
	publisher = {Springer},
	organization = {Springer},
	author = {Schmidt, S. and Kappes, J. H. and Bergtholdt, M. and Pekar, V. and Dries, S. and Bystrov, D. and Schn{\"o}rr, C.}
}
@incollection {falkenroth2007a,
	title = {Visualisation of oxygen concentration fields in the mass boundary layer by fluorescence quenching},
	year = {2007},
	publisher = {Springer Verlag},
	abstract = {Laser-Induced Fluorescence (LIF) is applied to observe directly the mechanism of gas exchange in the aqueous viscous boundary layer at a free water surface. In order to make dissolved oxygen visible, a new class of fluorescent dyes is used with a life time in the order of microseconds so that the quenching constant for dissolved oxygen is sufficiently high for sensitive measurements. Depth profiles of the O2 concentration near the water surface are obtained by a vertical laser sheet at a rate of 185 frames per second. This technique is capable of a measurement sector up to several centimetres down from the water surface with a resolution in the order of 50-100 um. For a small circular wind/wave facility a correlation between wind speed and gas-exchange rates calculated from the extrapolated mean boundary-layer thickness are presented as well as the results of parallel measurements with a budget method for other gases with known Schmidt numbers.},
	doi = {10.1007/978-3-540-36906-6_4},
	author = {A. Falkenroth and Kai Degreif and Bernd J{\"a}hne and Bernd J{\"a}hne},
	editor = {Christoph S. Garbe and Handler, R. A.}
}
@conference {zechmann_06_can,
	title = {Can man still beat the machine? Automated vs. manual pattern recognition of 3D MRSI data of prostate cancer patients},
	booktitle = {Proceedings of the 16th ISMRM},
	year = {2006},
	author = {C. M. Zechmann and B. Michael Kelm and Zamecnik, P. and Ikinger, U. and Waldherr, R. and R{\"o}ll, S. and Delorme, S. and Fred A. Hamprecht and Bachert, P.}
}
@article {lichy_06_einsatz,
	title = {Einsatz der 1H-MR-spektroskopischen Bildgebung in der Strahlentherapie: Cholin als Marker f{\"u}r die Bestimmung der relativen Wahrscheinlichkeit eines Tumorprogresses nach Bestrahlung glialer Hirntumoren},
	journal = {Zeitung f{\"u}r R{\"o}ntgenforschung},
	volume = {178},
	year = {2006},
	pages = {627-633},
	doi = {10.1055/s-2006-926744},
	author = {M. P. Lichy and Bachert, P. and Fred A. Hamprecht and M.-A. Weber and Debus, J. and Schulz-Ertner, D. and Kauczor, H.-U. and Schlemmer, H.-P.}
}
@conference {degreif2006a,
	title = {Gas exchange measurements: the chemically enhanced gas transfer of carbon dioxide at the water surface},
	booktitle = {Verhandlungen der Deutschen Physikalischen Gesellschaft, Spring Conference, Heidelberg, 15.-17.03.2006},
	year = {2006},
	publisher = {Deutsche Physikalische Gesellschaft},
	organization = {Deutsche Physikalische Gesellschaft},
	url = {http://www.dpg-verhandlungen.de/2006/heidelberg/up.html},
	author = {Kai Degreif and Joachim Kuss and Bernd J{\"a}hne}
}
@conference {degreif2006b,
	title = {Gas exchange measurements: transition of the boundary conditions from a flat to a rough water surface},
	booktitle = {Verhandlungen der Deutschen Physikalischen Gesellschaft, Spring Conference, Heidelberg, 15.-17.03.2006},
	year = {2006},
	publisher = {Deutsche Physikalische Gesellschaft},
	organization = {Deutsche Physikalische Gesellschaft},
	url = {http://www.dpg-verhandlungen.de/2006/heidelberg/up.html},
	author = {Kai Degreif and Bernd J{\"a}hne}
}
@phdthesis {degreif2006,
	title = {Untersuchungen zum Gasaustausch - Entwicklung und Applikation eines zeitlich aufgel{\"o}sten Massenbilanzverfahrens},
	year = {2006},
	publisher = {Institut f{\"u}r Umweltphysik, Fakult{\"a}t f{\"u}r Physik und Astronomie, Univ.\ Heidelberg},
	abstract = {The study presents a novel technique for measuring time resolved gas transfer rates at the water surface. By applying this new mass balance technique neither absolute concentrations of the trace gases nor the measurement of their concentrations in the water phase is required. Gas fluxes are calculated exclusively by the temporal change of the air-sided concentrations in an evasion experiment. The high temporal resolution of this procedure allows fast measurements under different conditions. Systematic measurements of gas exchange rates are now feasible within hours. By using UV-spectroscopy, simultaneous concentration measurements of volatile aromatics in the air and water phases verified the results obtained by the presented technique. Within the framework of the UV-measurements a method was developed to determine the air-sided concentrations of the aromatics precisely, even at low spectral resolution of the spectrometer. The differential optical absorption spectroscopy was successfully applied to a wide concentration range of these tracers. Reliable gas transfer velocities are now also available for very low wind speeds and friction velocities. The transition of the Schmidt number exponent from a flat to a rough water surface was reproduced. The transition begins at unexpectedly low wind speeds and extends over a wide range of wind speeds. For the first time the effect of chemically enhanced gas-exchange was demonstrated under a variety of chemical and physical conditions.},
	url = {http://www.ub.uni-heidelberg.de/archiv/6120},
	author = {Kai Degreif}
}
@conference {telea2006,
	title = {A variational approach to joint denoising, edge detection and motion estimation},
	booktitle = {Proceedings of the 28th DAGM Symposium on Pattern Recognition},
	year = {2006},
	pages = {525--535},
	url = {http://numod.ins.uni-bonn.de/research/papers/public/PrDrGa06.pdf},
	author = {Alexandru Telea and Tobias Preu{\ss}er and Christoph S. Garbe and Marc Droske and Martin Rumpf}
}
@conference {jaehne2005f,
	title = {The Heidelberg Aeolotron: new perspectives for laboratory investigations of small-scale air-sea interaction},
	booktitle = {Poster presented at: International Liege Colloquium on Ocean Dynamics, Gas Transfer at Water Surfaces},
	year = {2005},
	doi = {10.5281/zenodo.15417},
	author = {Bernd J{\"a}hne and Uwe Schimpf and Christoph S. Garbe and Kai Degreif}
}
@conference {klar2004a,
	title = {Analysis of subsurface gravel layer flow caused by turbulent open-channel flow using 3D PTV and pressure sensor techniques},
	booktitle = {BAW-Workshop Soil and Bed Stability - Interaction Effects between Geotechnics and Hydraulic Engineering},
	year = {2004},
	author = {Michael Klar and Markus Jehle and Bernd J{\"a}hne and Detert, M. and Jirka G. H.}
}
@conference {degreif2004,
	title = {Gas exchange experiments using time resolved UV-spectroscopy},
	booktitle = {Verhandlungen der Deutschen Physikalischen Gesellschaft, Spring Conference, Munich, 22.-26.03.2004},
	year = {2004},
	publisher = {Deutsche Physikalische Gesellschaft},
	organization = {Deutsche Physikalische Gesellschaft},
	abstract = {The air sea gas exchange plays a key role in the development of the earth{\textquoteright}s climate. The oceans can act as a source or sink for climate relevant gases such as carbon dioxide, methane or dimethyl sulphide. Hydrodynamics in the viscous boundary layer at the free ocean surface and therefore the gas transfer across the interface are not well understood yet. UV-spectroscopy provides a direct and fast measuring method for gaseous or volatile tracers in the air and water phase. A wide range of hydrodynamic parameters, i.e. Schmidt numbers and solubilities is feasible with volatile hydrocarbons such as benzene or fluorobenzene. Multiple tracers may be observed simultaneously with the same non-invasive measuring technique. Laboratory experiments are performed at a 120 cm diameter circular wind-wave-facility in Heidelberg. A detailed study of gas transfer rate{\textquoteright}s dependence on the mean squared surface wave slope s^2, friction velocity u*, as well as on the Schmidt number Sc and solubility of the tracers will be performed. Also the influence of surface films or an increased viscosity is going to be examined. Preliminary results and further prospects are presented.},
	url = {http://www.dpg-verhandlungen.de/2004/up_15.html},
	author = {Kai Degreif and Bernd J{\"a}hne}
}
@conference {detert2004,
	title = {Pressure fluctuations within subsurface gravel bed caused by turbulent open-channel flow},
	booktitle = {Proc. of River Flow 2004},
	year = {2004},
	pages = {695-701},
	publisher = {A. A. Balkema Publishers},
	organization = {A. A. Balkema Publishers},
	author = {Detert, M. and G. H. Jirka and Markus Jehle and Michael Klar and Bernd J{\"a}hne and H.-J. K{\"o}hler and Wenka, T.}
}
@conference {klar2004c,
	title = {Simultaneous 3D PTV and micro-pressure sensor equipment for flow analysis in subsurface gravel layer},
	booktitle = {Proc. of River Flow 2004},
	year = {2004},
	pages = {703--712},
	publisher = {A. A. Balkema Publishers},
	organization = {A. A. Balkema Publishers},
	author = {Michael Klar and Markus Jehle and Detert, M. and G. H. Jirka and Bernd J{\"a}hne and H.-J. K{\"o}hler and Wenka, T.}
}
@incollection {Ruhnau-et-al-04,
	title = {Variational Optical Flow Estimation for Particle Image Velocimetry},
	year = {2004},
	month = {Sept},
	publisher = {Deutsche Gesellschaft f{\"u}r Laser-Anemometrie GALA e.V.},
	chapter = {30},
	address = {Karlsruhe},
	author = {Ruhnau, P. and Kohlberger, T. and Nobach, H. and Schn{\"o}rr, C.},
	editor = {Ruck, B. and Leder, A. and Dopheide}
}
@incollection {scholes2003,
	title = {Biosphere-Atmosphere Interactions},
	year = {2003},
	pages = {19--71},
	publisher = {Springer},
	chapter = {2},
	doi = {10.1007/978-3-642-18984-5_2},
	author = {Mary C. Scholes and Patricia A. Matrai and Meinrat O. Andreae and Keith A. Smith and Martin R. Manning and Paulo Artaxo and Leonard A. Barrie and Timothy S. Bates and James H. Butler and Paolo Ciccioli and Stanislaw A. Cieslik and Robert J. Delmas and Frank J. Dentener},
	editor = {Guy P. Brasseur and Ronald G. Prinn and Alexander A. P. Pszenny}
}
@conference {long2002,
	title = {A closer look at short waves generated by wave interactions with adverse currents},
	booktitle = {Gas Transfer at Water Surfaces},
	volume = {127},
	year = {2002},
	pages = {121--128},
	publisher = {American Geophysical Union},
	organization = {American Geophysical Union},
	author = {S. R. Long and J. Klinke},
	editor = {E. S. Saltzman and M. A. Donelan and R. Wanninkhof and W. M. Drennan}
}
@conference {zappa2002,
	title = {Effect of microscale wave breaking on air-water gas transfer},
	booktitle = {Gas Transfer at Water Surfaces},
	volume = {127},
	year = {2002},
	pages = {23--29},
	publisher = {American Geophysical Union},
	organization = {American Geophysical Union},
	doi = {10.1029/GM127p0023},
	author = {Christopher J. Zappa and William E. Asher and Jessup, A. T. and J. Klinke and S. R. Long},
	editor = {E. S. Saltzman and M. A. Donelan and R. Wanninkhof and W. M. Drennan}
}
@phdthesis {dierig2002,
	title = {Gewinnung von Tiefenkarten aus Fokusserien},
	year = {2002},
	publisher = {IWR, Fakult{\"a}t f{\"u}r Physik und Astronomie, Univ.\ Heidelberg},
	url = {http://www.ub.uni-heidelberg.de/archiv/2461},
	author = {Tobias Dierig}
}
@conference {schimpf2002a,
	title = {On the investigations of statistical properties of the micro turbulence at the ocean surface},
	booktitle = {Gas Transfer at Water Surfaces},
	volume = {127},
	year = {2002},
	pages = {51--57},
	publisher = {American Geophysical Union},
	organization = {American Geophysical Union},
	doi = {10.1029/GM127p0051},
	author = {Uwe Schimpf and Bernd J{\"a}hne and Horst Hau{\ss}ecker},
	editor = {E. S. Saltzman and M. A. Donelan and R. Wanninkhof and W. M. Drennan}
}
@conference {spies2002a,
	title = {Local models for dynamic processes in image sequences},
	booktitle = {Dynamic Perception},
	year = {2002},
	pages = {59--64},
	publisher = {Aka GmbH},
	organization = {Aka GmbH},
	author = {Hagen Spies and Tobias Dierig and Christoph S. Garbe and W{\"u}rtz, R. P.},
	editor = {Lappe, M.}
}
@conference {garbe2002a,
	title = {Measuring the sea surface heat flux and probability distribution of surface renewal events},
	booktitle = {Gas Transfer at Water Surfaces},
	volume = {127},
	year = {2002},
	pages = {109-114},
	publisher = {American Geophysical Union},
	organization = {American Geophysical Union},
	doi = {10.1029/GM127p0109},
	author = {Christoph S. Garbe and Horst Hau{\ss}ecker and Bernd J{\"a}hne},
	editor = {E. S. Saltzman and M. A. Donelan and R. Wanninkhof and W. M. Drennan}
}
@article {gee_02_molecular,
	title = {A molecular dynamics simulation study of the conformational preferences of oligo-(3- hydroxyalcanoic acids) in chloroform solution},
	journal = {Helv. Chim. Acta},
	volume = {85},
	year = {2002},
	pages = {618-632},
	author = {Gee, P. J. and Fred A. Hamprecht and Schuler, L. D. and van Gunsteren, W. F. and Duchardt, E. and Schwalbe, H. and Albert, M. and Seebach, D.}
}
@conference {bock2002,
	title = {Overview of the CoOP experiments: physical and chemical measurements parameterizing air-sea gas transfer},
	booktitle = {Gas Transfer at Water Surfaces},
	volume = {127},
	year = {2002},
	pages = {39--44},
	publisher = {American Geophysical Union},
	organization = {American Geophysical Union},
	doi = {10.1029/GM127p0039},
	author = {E. J. Bock and J. B. Edson and Nelson M. Frew and T. Hara and Horst Hau{\ss}ecker and Bernd J{\"a}hne and W. R. McGilles and S. P. McKenna and R. K. Nelson and Uwe Schimpf and B. M. Uz},
	editor = {M. A. Donelan and W. M. Drennan and R. Wanninkhof and E. S. Saltzman}
}
@conference {haussecker2002,
	title = {Physics from IR image sequences: Quantitative analysis of transport models and parameters of air-sea gas transfer},
	booktitle = {Gas Transfer at Water Surfaces},
	volume = {127},
	year = {2002},
	note = {invited},
	pages = {103--108},
	publisher = {American Geophysical Union},
	organization = {American Geophysical Union},
	doi = {10.1029/GM127p0103},
	author = {Horst Hau{\ss}ecker and Uwe Schimpf and Christoph S. Garbe and Bernd J{\"a}hne},
	editor = {E. S. Saltzman and M. A. Donelan and R. Wanninkhof and W. M. Drennan}
}
@conference {hara2002a,
	title = {Surface wave observations during CoOP experiments and their relations to air-sea gas transfer},
	booktitle = {Gas Transfer at Water Surfaces},
	volume = {127},
	year = {2002},
	pages = {45--49},
	publisher = {American Geophysical Union},
	organization = {American Geophysical Union},
	author = {T. Hara and B. M. Uz and H. Wei and J. B. Edson and Nelson M. Frew and W. R. McGilles and S. P. McKenna and E. J. Bock and Horst Hau{\ss}ecker and Uwe Schimpf},
	editor = {M. A. Donelan and W. M. Drennan and R. Wanninkhof and E. S. Saltzman}
}
@article {hamprecht_01_strategy,
	title = {A strategy for analysis of (molecular) equilibrium simulations: configuration space density estimation, clustering and visualization},
	journal = {Journal of Chemical Physics},
	volume = {114},
	year = {2001},
	pages = {2079-2089},
	author = {Fred A. Hamprecht and Peter, C. and Daura, X. and Thiel, W. and van Gunsteren, W. F.}
}
@incollection {kuemmerlen2000,
	title = {Thermography to measure water relations of plant leaves},
	year = {2000},
	pages = {636--637},
	publisher = {Academic Press},
	chapter = {A14},
	author = {Bernd K{\"u}mmerlen and Stefan Dauwe and Dominik Schmund and Ulrich Schurr and Bernd J{\"a}hne and Horst Hau{\ss}ecker}
}
@incollection {geissler2000c,
	title = {Three-dimensional imaging algorithms},
	year = {2000},
	pages = {397--438},
	publisher = {Academic Press},
	chapter = {11},
	author = {Peter Gei{\ss}ler and Tobias Dierig and Hanspeter A. Mallot and Bernd J{\"a}hne},
	editor = {Hau\DFecker, H.}
}
@incollection {jaehne1999,
	title = {Bl{\"a}tter, Wind und Wellen. Unsichtbares wird sichtbar.},
	year = {1999},
	pages = {38--43},
	publisher = {dot-Verlag},
	author = {Bernd J{\"a}hne},
	editor = {G. Dotzler}
}
@incollection {kuemmerlen1999,
	title = {Thermography to measure water relations of plant leaves},
	volume = {3: Systems and Applications},
	year = {1999},
	pages = {763-781},
	publisher = {Academic Press},
	chapter = {36},
	author = {Bernd K{\"u}mmerlen and Stefan Dauwe and Dominik Schmund and Ulrich Schurr and Bernd J{\"a}hne and Peter Gei{\ss}ler and Horst Hau{\ss}ecker}
}
@phdthesis {dieter1998,
	title = {Analysis of Small-Scale Ocean Wind Waves by Image Sequence Analysis of Specular Reflections},
	year = {1998},
	publisher = {IWR, Fakult{\"a}t f{\"u}r Physik und Astronomie, Univ.\ Heidelberg},
	url = {http://d-nb.info/955455804},
	author = {Jochen Dieter}
}
@conference {hering1997,
	title = {A comprehensive study of algorithms for multidimensional flow field diagnostics},
	booktitle = {Proc. Optical 3D Measurement Techniques IV, Zurich, Sept. 29 - Oct. 2, 1997},
	year = {1997},
	pages = {436--443},
	publisher = {Wichmann},
	organization = {Wichmann},
	author = {Frank Hering and Horst Hau{\ss}ecker and Jochen Dieter and T. Netzsch and Bernd J{\"a}hne},
	editor = {A. Gr{\"u}n and H. Kahmen}
}
@mastersthesis {dauwe1997,
	title = {Infrarotuntersuchungen zur Bestimmung des Wasser- und W{\"a}rmehaushalts eines Blattes},
	year = {1997},
	school = {University of Heidelberg},
	author = {Stefan Dauwe}
}
@conference {dieter1997,
	title = {Measurements of slope statistics on a wind driven water surface},
	booktitle = {Optical 3D Measurement Techniques 4 - Applications in architecture, quality control, robotics, navigation, medical imaging and animation},
	year = {1997},
	publisher = {Wichmann},
	organization = {Wichmann},
	author = {Jochen Dieter and Lauer, Hermann and Bernd J{\"a}hne and A. Gr{\"u}n},
	editor = {H. Kahmen}
}
@incollection {liss1997,
	title = {Report Group 1 - Physical processes in the microlayer and the air-sea exchange of trace gases},
	year = {1997},
	pages = {1--33},
	publisher = {Cambridge University Press},
	doi = {10.1017/CBO9780511525025.002},
	author = {Peter S. Liss and A. J. Watson and E. J. Bock and Bernd J{\"a}hne and William E. Asher and Nelson M. Frew and L. Hasse and Gerald M. Korenowski and L. Merlivat and L. F. Phillips and P. Schl{\"u}ssel and D. K. Woolf},
	editor = {Peter S. Liss and Robert A. Duce}
}
@conference {Gerloff-et-al-97,
	title = {Semi{\textendash}Automated Analysis of SXM Images},
	booktitle = {Proc. 9th Int. Conf. on Scanning Tunneling Microscopy/Spectroscopy and Related Techniques (STM{\textquoteright}97)},
	year = {1997},
	month = {July, 20{\textendash}25},
	address = {Hamburg, Germany},
	author = {Gerloff, S. and Hagemann, A. and Schn{\"o}rr, C. and Tieck, S. and Stiehl, H.S. and Dombrowski, R. and Dreyer, M. and Wiesendanger, R.}
}
@conference {waas1996,
	title = {Combined height/slope/curvature measurements of short ocean wind waves},
	booktitle = {Proc.\ The Air-Sea Interface, Radio and Acoustic Sensing, Turbulence and Wave Dynamics, Marseille, 24--30. June 1993},
	year = {1996},
	pages = {383--388},
	publisher = {RSMAS, University of Miami},
	organization = {RSMAS, University of Miami},
	doi = {10.5281/zenodo.14000},
	author = {Stefan Waas and Bernd J{\"a}hne},
	editor = {M. A. Donelan and W. H. Hui and W. J. Plant}
}
@conference {hering1996b,
	title = {Combined wave and flow field visualization for investigation of short-wave/long-wave interaction},
	booktitle = {Proc.\ The Air-Sea Interface, Radio and Acoustic Sensing, Turbulence and Wave Dynamics, Marseille, 24--30. June 1993},
	year = {1996},
	pages = {133--138},
	publisher = {RSMAS, University of Miami},
	organization = {RSMAS, University of Miami},
	doi = {10.5281/zenodo.14002},
	author = {Frank Hering and Dietmar Wierzimok and W. K. Melville and Bernd J{\"a}hne},
	editor = {M. A. Donelan and W. H. Hui and W. J. Plant}
}
@conference {spedding1996,
	title = {Estimating $\omega(k)$ in an unsteady, wind-generated surface wave field from the 2D complex wavelet transform of the surface slope},
	booktitle = {Proc.\ The Air-Sea Interface, Radio and Acoustic Sensing, Turbulence and Wave Dynamics, Marseille, 24--30. June 1993},
	year = {1996},
	pages = {373--382},
	publisher = {RSMAS, University of Miami},
	organization = {RSMAS, University of Miami},
	doi = {10.5281/zenodo.14564},
	author = {G. R. Spedding and J. Klinke and S. R. Long},
	editor = {M. A. Donelan and W. H. Hui and W. J. Plant}
}
@conference {muensterer1996a,
	title = {A fluorescence technique to measure concentration profiles in the aqueous mass boundary layer},
	booktitle = {Proc.\ The Air-Sea Interface, Radio and Acoustic Sensing, Turbulence and Wave Dynamics, Marseille, 24--30. June 1993},
	year = {1996},
	pages = {517--522},
	publisher = {RSMAS, University of Miami},
	organization = {RSMAS, University of Miami},
	doi = {10.5281/zenodo.13995},
	author = {Thomas M{\"u}nsterer and Bernd J{\"a}hne},
	editor = {M. A. Donelan and W. H. Hui and W. J. Plant}
}
@conference {jaehne1996b,
	title = {Measurements of the modulation of short waves from image sequences},
	booktitle = {Proc.\ The Air-Sea Interface, Radio and Acoustic Sensing, Turbulence and Wave Dynamics, Marseille, 24--30. June 1993},
	year = {1996},
	pages = {389--394},
	publisher = {RSMAS, University of Miami},
	organization = {RSMAS, University of Miami},
	doi = {10.5281/zenodo.13996},
	author = {Bernd J{\"a}hne},
	editor = {M. A. Donelan and W. H. Hui and W. J. Plant}
}
@conference {janssen1996,
	title = {The VIERS scatterometer algorithm},
	booktitle = {Proc.\ The Air-Sea Interface, Radio and Acoustic Sensing, Turbulence and Wave Dynamics, Marseille, 24--30. June 1993},
	year = {1996},
	pages = {749--754},
	publisher = {RSMAS, University of Miami},
	organization = {RSMAS, University of Miami},
	doi = {10.5281/zenodo.13994},
	author = {J. A. M. Janssen and C. J. Calkoen and van Halsema, D. and Bernd J{\"a}hne and P. A. E. M. Janssen and W. A. Oost and P. Snoeij and J. Vogelzang and H. Wallbrink},
	editor = {M. A. Donelan and W. H. Hui and W. J. Plant}
}
@conference {klinke1996a,
	title = {Wave number spectra of short wind waves: implications from laboratory studies},
	booktitle = {Proc.\ The Air-Sea Interface, Radio and Acoustic Sensing, Turbulence and Wave Dynamics, Marseille, 24--30. June 1993},
	year = {1996},
	pages = {367--372},
	publisher = {RSMAS, University of Miami},
	organization = {RSMAS, University of Miami},
	doi = {10.5281/zenodo.14001},
	author = {J. Klinke and Bernd J{\"a}hne},
	editor = {M. A. Donelan and W. H. Hui and W. J. Plant}
}
@conference {bock1995b,
	title = {Description of the science plan for the April 1995 CoOP experiment, {\textquoteleft}gas transfer in coastal waters{\textquoteright}, performed from the research vessel New Horizon},
	booktitle = {Air-Water Gas Transfer, Selected Papers, 3rd Intern. Symp. on Air-Water Gas Transfer},
	year = {1995},
	pages = {801--810},
	publisher = {AEON},
	organization = {AEON},
	doi = {10.5281/zenodo.10408},
	author = {E. J. Bock and J. B. Edson and Nelson M. Frew and A. Karachintsev and W. R. McGilles and R. K. Nelson and K. Hansen and Bernd J{\"a}hne and T. Hara and B. M. Uz and Bernd J{\"a}hne and Jochen Dieter and J. Klinke and Horst Hau{\ss}ecker},
	editor = {E. C. Monahan}
}
@conference {dieter1995,
	title = {Measurements of velocity profiles in the aqueous boundary layer at a wind-driven water surface},
	booktitle = {Air-Water Gas Transfer, Selected Papers, 3rd Intern. Symp. on Air-Water Gas Transfer},
	year = {1995},
	pages = {145--152},
	publisher = {AEON},
	organization = {AEON},
	doi = {10.5281/zenodo.10393},
	author = {Jochen Dieter and Frank Hering and Roland Bremeyer and Bernd J{\"a}hne and Bernd J{\"a}hne},
	editor = {E. C. Monahan}
}
@conference {dieter1994a,
	title = {Flow measurements close to the free air/sea interface},
	booktitle = {Proceedings of the 7th International Symposium on Applications of Laser Techniques to Fluid Mechanics, Lisbon, Portugal, July 11.--14. 1994},
	volume = {II},
	year = {1994},
	pages = {22.2.1--6},
	author = {Jochen Dieter and Roland Bremeyer and Frank Hering}
}
@mastersthesis {dieter1994,
	title = {Messung von Str{\"o}mungen in der viskosen Grenzschicht an der Wasseroberfl{\"a}che},
	year = {1994},
	note = {IUP D-413},
	school = {Institut f{\"u}r Umweltphysik, Fakult{\"a}t f{\"u}r Physik und Astronomie, Univ.\ Heidelberg},
	author = {Jochen Dieter}
}
@conference {janssen1993,
	title = {The VIERS scatterometer algorithm},
	booktitle = {Proc. The Air-Sea Interface, Radio and Acoustic Sensing, Turbulence and Wave Dynamics, Marseille, 24--30. June 1993},
	year = {1993},
	pages = {749--754},
	publisher = {University of Miami},
	organization = {University of Miami},
	doi = {10.5281/zenodo.13994},
	author = {J. A. M. Janssen and C. J. Calkoen and van Halsema, D. and Bernd J{\"a}hne and P. A. E. M. Janssen and W. A. Oost and P. Snoeij and J. Vogelzang and H. Wallbrink},
	editor = {M. A. Donelan and W. H. Hui and W. J. Plant}
}
@conference {halsema1988,
	title = {VIERS-1: A Programme of Wind Scatterometry},
	booktitle = {Geoscience and Remote Sensing Symposium, Proc.\ IGARSS{\textquoteright}88},
	volume = {1},
	year = {1988},
	pages = {572},
	doi = {10.1109/IGARSS.1988.570207},
	author = {van Halsema, D. and de Loor, P. and Bernd J{\"a}hne}
}
@conference {wierzimok1987,
	title = {Bildfolgenanalyse dreidimensionaler turbulenter Str{\"o}mungen},
	booktitle = {Proc. 9. DAGM-Symposium zur Mustererkennung 1987},
	volume = {149},
	year = {1987},
	pages = {288},
	publisher = {Springer},
	organization = {Springer},
	doi = {10.1007/978-3-662-22205-8_71},
	author = {Dietmar Wierzimok and Bernd J{\"a}hne and J. Dengler},
	editor = {E. Paulus}
}
@article {jaehne1987a,
	title = {Measurement of the diffusion coefficients of sparingly soluble gases in water},
	journal = {J. Geophys. Res.},
	volume = {92},
	number = {C10},
	year = {1987},
	pages = {10,767--10,776},
	abstract = {The diffusion coefficients D of important gas tracers dissolved in water and seawater were measured with a modified Barrer method. The measurements include the gases He, Ne, Kr, Xe, H2, CH4, and CO2 dissolved in distilled water in the temperature range from 5 to 35{\textdegree}C, and He and H2 dissolved in seawater in the same temperature range. The maximum systematic error is estimated to be well below 5\%. The isotopic fractionation in the diffusion coefficient was determined to be (0.87 {\textpm} 0.05) for 13CO2/12CO2 and (15 {\textpm} 3)\% for 3He/4He.},
	doi = {10.1029/JC092iC10p10767},
	author = {Bernd J{\"a}hne and Gerhard Heinz and Wolfgang Dietrich}
}
@article {jaehne1987b,
	title = {On the parameters influencing air-water gas exchange},
	journal = {J. Geophys. Res.},
	volume = {92},
	year = {1987},
	pages = {1937--1950},
	abstract = {Detailed gas exchange measurements from two circular and one linear wind/wave tunnels are presented. Heat, He, CH4, CO2, Kr, and Xe have been used as tracers. The experiments show the central importance of waves for the water-side transfer process. With the onset of waves the Schmidt number dependence of the transfer velocity k changes from k proportional to Sc^-2/3 to k proportional to Sc^-1/2 indicating a change in the boundary conditions at the surface. Moreover, energy put into the wave field by wind is transferred to near-surface turbulence enhancing gas transfer. The data show that the mean square slope of the waves is the best parameter to characterize the free wavy surface with respect to water-side transfer processes.},
	doi = {10.1029/JC092iC02p01937},
	author = {Bernd J{\"a}hne and K. O. M{\"u}nnich and R. B{\"o}singer and A. Dutzi and Werner A. Huber and P. Libner}
}
@mastersthesis {dutzi1984,
	title = {Untersuchungen zum Einfluss der Temperatur auf den Gasaustausch},
	year = {1984},
	note = {IUP D-190},
	school = {Institut f{\"u}r Umweltphysik, Fakult{\"a}t f{\"u}r Physik und Astronomie, Univ.\ Heidelberg},
	doi = {10.5281/zenodo.14919},
	author = {A. Dutzi}
}
@conference {jaehne1984b,
	title = {Wind/wave-tunnel experiments on the Schmidt number and wave field dependence of air-water gas exchange},
	booktitle = {Gas transfer at water surfaces},
	year = {1984},
	pages = {303--309},
	publisher = {Reidel},
	organization = {Reidel},
	doi = {10.1007/978-94-017-1660-4_28},
	author = {Bernd J{\"a}hne and Werner A. Huber and A. Dutzi and Thomas Wais and Johann Ilmberger},
	editor = {W. Brutsaert and G. H. Jirka}
}
@mastersthesis {dietrich1983,
	title = {Aufbau und Erprobung eines neuartigen Diaphragmaverfahrens zur Messung der Diffusionskonstanten von in Wasser gel{\"o}sten Gasen},
	year = {1983},
	note = {IUP D-176},
	school = {Institut f{\"u}r Umweltphysik, Fakult{\"a}t f{\"u}r Physik und Astronomie, Univ.\ Heidelberg},
	author = {Wolfgang Dietrich}
}
