@unpublished {7061,
	title = {Evidential Turing Processes},
	number = {https://arxiv.org/abs/2106.01216},
	year = {2021},
	publisher = {arXiv preprint},
	url = {https://arxiv.org/abs/2106.01216},
	author = {Kandemir, M and Agk{\"u}l, A and Hau{\ss}mann, M and {\"U}nal, G}
}
@article {7022,
	title = {Microscopy-based assay for semi-quantitative detection of SARS-CoV-2 specific antibodies in human sera},
	journal = {BioEssays},
	volume = {43},
	year = {2021},
	doi = {10.1002/bies.202000257},
	author = {Pape, C and Remme, R and Wolny, A and Olberg, S and Wolf, S and Cerrone, L and Cortese, M and Klaus, S and Lucic, B and Ullrich, S and Anders-{\"O}sswein, M and Wolf, S and Cerikan, B and Neufeldt, C J and Ganter, M and Schnitzler, P and Merle, U and Lusic, M and Boulant, S and Stanifer, M and Bartenschlager, R and Hamprecht, F A and Kreshuk, A and Tischer, C and Kr{\"a}usslich, H.-G. and M{\"u}ller, B and Laketa, V}
}
@proceedings {7064,
	title = {Object Retrieval and Localization in Large Art Collections Using Deep Multi-style Feature Fusion and Iterative Voting},
	year = {2020},
	month = {08-2020},
	abstract = {The search for specific objects or motifs is essential to art history as both assist in decoding the meaning of artworks. Digitization has produced large art collections, but manual methods prove to be insufficient to analyze them. In the following, we introduce an algorithm that allows users to search for image regions containing specific motifs or objects and find similar regions in an extensive dataset, helping art historians to analyze large digitized art collections. Computer vision has presented efficient methods for visual instance retrieval across photographs. However, applied to art collections, they reveal severe deficiencies because of diverse motifs and massive domain shifts induced by differences in techniques, materials, and styles. In this paper, we present a multi-style feature fusion approach that successfully reduces the domain gap and improves retrieval results without labelled data or curated image collections. Our region-based voting with GPU-accelerated approximate nearest-neighbour search allows us to find and localize even small motifs within an extensive dataset in a few seconds. We obtain state-of-the-art results on the Brueghel dataset and demonstrate its generalization to inhomogeneous collections with a large number of distractors.},
	doi = {https://doi.org/10.1007/978-3-030-66096-3_12},
	author = {Nikolai Ufer and Sabine Lang and Bj{\"o}rn Ommer}
}
@conference {6324,
	title = {Weakly Supervised Learning of Dense SemanticCorrespondences and Segmentation},
	booktitle = {German Conference on Pattern Recognition (GCPR)},
	year = {2019},
	author = {Nikolai Ufer and Kam To Lui and Katja Schwarz and Paul Warkentin and Bj{\"o}rn Ommer}
}
@article {fortun2018fast,
	title = {Fast Piecewise-Affine Motion Estimation Without Segmentation},
	journal = {IEEE Transactions on Image Processing},
	volume = {27 },
	year = {2018},
	pages = {5612 - 5624},
	author = {Denis Fortun and Martin Storath and Dennis Rickert and Andreas Weinmann and Michael Unser}
}
@conference {6136,
	title = {Deep Semantic Feature Matching},
	booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
	year = {2017},
	author = {Nikolai Ufer and Bj{\"o}rn Ommer}
}
@proceedings {6182,
	title = {Diverse M-best Solutions by Dynamic Programming},
	volume = {LNCS 10496},
	year = {2017},
	pages = {255-267},
	publisher = {Springer},
	doi = {10.1007/978-3-319-66709-6_21},
	author = {Haubold, C. and Uhlmann, V and Michael Unser and Fred A. Hamprecht}
}
@article {6209,
	title = {Diverse Shortest Paths for Bioimage Analysis},
	journal = {Bioinformatics},
	year = {2017},
	pages = {1-3},
	doi = {10.1093/bioinformatics/btx621},
	author = {Uhlmann, V and Haubold, C. and Fred A. Hamprecht and Michael Unser}
}
@article {storath2016fast,
	title = {Fast segmentation from blurred data in {3D} fluorescence microscopy},
	journal = {IEEE Transactions on Image Processing},
	volume = {26},
	year = {2017},
	month = {06/2017},
	chapter = { 4856 - 4870},
	doi = {10.1109/TIP.2017.2716843},
	author = {Martin Storath and Dennis Rickert and Michael Unser and Andreas Weinmann}
}
@conference {Levinkov2017,
	title = {Joint graph decomposition \& node labeling: Problem, algorithms, applications},
	booktitle = {Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017},
	volume = {2017-Janua},
	year = {2017},
	pages = {1904{\textendash}1912},
	abstract = {We state a combinatorial optimization problem whose feasible solutions define both a decomposition and a node labeling of a given graph. This problem offers a common mathematical abstraction of seemingly unrelated computer vision tasks, including instance-separating semantic segmentation, articulated human body pose estimation and multiple object tracking. Conceptually, the problem we state generalizes the unconstrained integer quadratic program and the minimum cost lifted multicut problem, both of which are NP-hard. In order to find feasible solutions efficiently, we define two local search algorithms that converge monotonously to a local optimum, offering a feasible solution at any time. To demonstrate their effectiveness in tackling computer vision tasks, we apply these algorithms to instances of the problem that we construct from published data, using published algorithms. We report state-of-the-art application-specific accuracy for the three above-mentioned applications.},
	isbn = {9781538604571},
	doi = {10.1109/CVPR.2017.206},
	author = {Levinkov, Evgeny and Uhrig, Jonas and Tang, Siyu and Omran, Mohamed and Insafutdinov, Eldar and Kirillov, Alexander and Carsten Rother and Brox, Thomas and Schiele, Bernt and Bj{\"o}rn Andres}
}
@article {storath2016jump,
	title = {Jump-penalized least absolute values estimation of scalar or circle-valued signals},
	journal = {Information and Inference},
	volume = {6},
	year = {2017},
	pages = {225{\textendash}245},
	doi = {10.1093/imaiai/iaw022},
	author = {Martin Storath and Andreas Weinmann and Michael Unser}
}
@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.}
}
@article {kleesiek_16_deep,
	title = {Deep MRI brain extraction: A 3D convolutional neural network for skull stripping.},
	journal = {NeuroImage},
	volume = {129},
	year = {2016},
	pages = {460-469},
	doi = {10.1016/j.neuroimage.2016.01.024},
	author = {Kleesiek, J and Urban, G and Hubert, A and Schwarz, D and Maier-Hein, K and M. Bendszus and A. Biller}
}
@conference {kleesiek_14_ilastik,
	title = {ilastik for Multi-modal Brain Tumor Segmentation},
	booktitle = {MICCAI BraTS (Brain Tumor Segmentation) Challenge. Proceedings, 3rdplace},
	year = {2014},
	pages = {12-17},
	author = {Kleesiek, J. and A. Biller and Urban, G. and Ullrich K{\"o}the and M. Bendszus and Fred A. Hamprecht}
}
@conference {urban_14_multi-modal,
	title = {Multi-modal Brain Tumor Segmentation using Deep Convolutional NeuralNetworks},
	booktitle = {MICCAI BraTS (Brain Tumor Segmentation) Challenge. Proceedings, winningcontribution},
	year = {2014},
	pages = {31-35},
	author = {Urban, G. and M. Bendszus and Fred A. Hamprecht and Kleesiek, J.}
}
@mastersthesis {urban_14_neural,
	title = {Neural Networks: Optimization and Applications},
	year = {2014},
	school = {University of Heidelberg},
	author = {Urban, G.}
}
@incollection {jaehne2012,
	title = {Gas transfer at water surfaces},
	year = {2012},
	pages = {389--404},
	publisher = {CRC Press/Balkema},
	chapter = {22},
	url = {http://www.crcnetbase.com/isbn/9780203803967},
	author = {Bernd J{\"a}hne},
	editor = {W. Rodi and M. Uhlmann}
}
@conference {menze_07_classification,
	title = {Classification of multispectral ASTER imagery in the archaeological survey for settlement sites of the Near East},
	booktitle = {Proc 10th International Symposium on Physical Measurements and Signature in Remote Sensing (ISPMRS 07), Davos, Switzerland},
	year = {2007},
	note = {1},
	publisher = {International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences},
	organization = {International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences},
	author = {Bjoern H. Menze and Ur, J. A.}
}
@article {menze_06_detection,
	title = {Detection of ancient settlement mounds - Archaeological survey based on the SRTM terrain model},
	journal = {Photgrammetric Engineering \& Remote Sensing},
	volume = {3},
	year = {2006},
	note = {1},
	pages = {321-327},
	author = {Bjoern H. Menze and Ur, J. A. and Sherratt, A. G.}
}
@conference {menze_05_tell,
	title = {Tell Spotting - Surveying Near Eastern Settlement Mounds from Space},
	booktitle = {Proceedings of the XXth CIPA International Symposium 2005, Torino, Italy},
	year = {2005},
	note = {1},
	pages = {217-223},
	author = {Bjoern H. Menze and Ur, J. A. and Sherratt, A. G.}
}
@article {frew2004,
	title = {Air-sea gas transfer: Its dependence on wind stress, small-scale roughness, and surface films},
	journal = {J. Geophys. Res.},
	volume = {109},
	year = {2004},
	pages = {C08S17},
	doi = {10.1029/2003JC002131},
	author = {Nelson M. Frew and E. J. Bock and Uwe Schimpf and T. Hara and Horst Hau{\ss}ecker and J. B. Edson and W. R. McGilles and R. K. Nelson and S. P. McKenna and B. M. Uz and Bernd J{\"a}hne}
}
@article {uttenweiler2003a,
	title = {Spatiotemporal anisotropic diffusion filtering to improve signal-to-noise ratios and object restoration in fluorescence microscopic image sequences.},
	journal = {J Biomed Opt},
	volume = {8},
	number = {1},
	year = {2003},
	pages = {40--47},
	publisher = {Ruprecht-Karls-Universit{\"a}t Heidelberg, Institut f{\"u}r Physiologie und Pathophysiologie Medical Biophysics, Im Neuenheimer Feld 326, 69120 Heidelberg, Germany. dietmar.uttenweiler@urz.uni-heidelberg.de},
	abstract = {We present an approach for significantly improving the quantitative analysis of motion in noisy fluorescence microscopic image sequences. The new partial differential equation based method is a general extension of a 2-D nonlinear anisotropic diffusion filtering scheme to a specially adapted 3D nonlinear anisotropic diffusion filtering scheme, with two spatial image dimensions and the time t in the image sequence as the third dimension. Motion in image sequences is considered as oriented, line-like structures in the spatiotemporal x,y,t domain, which are determined by the structure tensor method. Image enhancement is achieved by a structure adopted smoothing kernel in three dimensions, thereby using the full 3D information inherent in spatiotemporal image sequences. As an example for low signal-to-noise ratio (SNR) microscopic image sequences we have applied this method to noisy in vitro motility assay data, where fluorescently labeled actin filaments move over a surface of immobilized myosin. With the 3D anisotropic diffusion filtering the SNR is significantly improved (by a factor of 3.8) and closed object structures are reliably restored, which were originally degraded by noise. Generally, this approach is very valuable for all applications where motion has to be measured quantitatively in low light level fluorescence microscopic image sequences of cellular, subcellular, and molecular processes.},
	doi = {10.1117/1.1527627},
	url = {http://dx.doi.org/10.1117/1.1527627},
	author = {D. Uttenweiler and C. Weber and Bernd J{\"a}hne and Rainer H. A. Fink and Schaar, H.}
}
@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 {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}
}
@conference {raisch2002,
	title = {Velocity and feature estimation of actin filaments using active contours in noisy fluorescence image sequences},
	booktitle = {Proc. 2nd IASTED Int. Conf. Visualization, Imaging and Image Processing},
	year = {2002},
	pages = {645--650},
	abstract = {We present a new approach for determining particle fea tures such as length, curvature and hence flexibility in addition to the velocity of moving single actin filaments in noisy fluorescence image sequences. The reliable deter mination of these features is essential for the analysis of the elementary force generation process of single motor molecules including heart and skeletal muscle myosins. First, the image sequence is preprocessed with the 3D structure tensor - where the third dimension is the time t in the image sequence - in order to eliminate noise and to obtain a measure for extracting coherently moving par ticles. Secondly, we determine the contour of the actin filaments with subpixel accuracy using active contours. Thereafter, we readjust a local coordinate system to elim inate inner movements of the active contour. In the fourth step, we estimate the initial position of the active contour in the next frame from the displacement vector field cal culated by the 3D structure tensor. The accuracy of the method is verified on synthetic test data, a prerequisite for the quantitative use of this method on experimentally obtained data. Finally this is demonstrated for fluorescence image sequences of actin filament movement in the in vitro motility assay.},
	author = {Florian Raisch and Hanno Scharr and Norbert Kirchge{\ss}ner and Bernd J{\"a}hne and Rainer H. A. Fink and D. Uttenweiler}
}
@article {uttenweiler2000,
	title = {Motion determination in actin filament fluorescence images with a spatio-temporal orientation analysis method.},
	journal = {Biophys J},
	volume = {78},
	number = {5},
	year = {2000},
	pages = {2709--2715},
	publisher = {Institut f{\"u}r Physiologie und Pathophysiologie, Ruprecht-Karls-Universit{\"a}t Heidelberg, 69120 Heidelberg, Germany. uttenweiler@urz.uni-heidelberg.de},
	abstract = {We present a novel approach of automatically measuring motion in series of microscopic fluorescence images. As a differential method, the three-dimensional structure tensor technique is used to calculate the displacement vector field for every image of the sequence, from which the velocities are subsequently derived. We have used this method for the analysis of the movement of single actin filaments in the in vitro motility assay, where fluorescently labeled actin filaments move over a myosin decorated surface. With its fast implementation and subpixel accuracy, this approach is, in general, very valuable for analyzing dynamic processes by image sequence analysis.},
	doi = {10.1016/S0006-3495(00)76815-9},
	author = {D. Uttenweiler and C. Veigel and R. Steubing and Carlo G{\"o}tz and Sven Mann and Horst Hau{\ss}ecker and Bernd J{\"a}hne and Rainer H. A. Fink}
}
@article {schurr1996,
	title = {Structural and functional evidence for xylem-mediated water transport and high tranpiration in Agrobacterium tumefaciens-induced tumors of Ricinus communis},
	journal = {Botanica Acta},
	volume = {109},
	year = {1996},
	pages = {405--412},
	doi = {10.1111/j.1438-8677.1996.tb00590.x},
	author = {Ulrich Schurr and B. Schuberth and R. Aloni and K. S. Pradel and Dominik Schmund and Bernd J{\"a}hne and C. I. Ullrich}
}
@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}
}
