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Author Title [ Type(Desc)] Year
Journal Article
Berg, S, Kutra, D, Kroeger, T, Straehle, C N, Kausler, B X, Haubold, C, Schiegg, M, Ales, J, Beier, T, Rudy, M, Eren, K, Cervantes, J I, Xu, B, Beuttenmüller, F, Wolny, A, Zhang, C, Köthe, U, Hamprecht, F A and Kreshuk, A (2019). ilastik: interactive machine learning for (bio)image analysis. Nature Methods. 16 1226-1232
Hühnerbein, R, Savarino, F, Aström, F and Schnörr, C (2018). Image Labeling Based on Graphical Models Using Wasserstein Messages and Geometric Assignment. SIAM Journal on Imaging Sciences. 11 1317-1362PDF icon Technical Report (2.62 MB)
Hühnerbein, R, Savarino, F, Aström, F and Schnörr, C (2018). Image Labeling Based on Graphical Models Using Wasserstein Messages and Geometric Assignment. SIAM J. Imaging Science. 11 1317–1362. https://epubs.siam.org/doi/abs/10.1137/17M1150669
Aström, F, Petra, S, Schmitzer, B and Schnörr, C (2017). Image Labeling by Assignment. J. Math. Imag. Vision. 58 211–238. Papers/Astroem2017.pdf
Frank, M and Hamprecht, F A (2011). Image-Based Supervision of a Periodically Working Machine. Pattern Analysis and Applications. 1-10PDF icon Technical Report (466.61 KB)
Jähne, B, Klinke, J and Waas, S (1994). Imaging of short ocean wind waves: a critical theoretical review. J. Opt. Soc. Am. A. 11 2197--2209
Meijering, E, Carpenter, A E, Peng, H, Hamprecht, F A and Olivo-Marin, J (2016). Imagining the future of bioimage analysis. Nature Biotechnology. 34 1250-1255PDF icon Technical Report (924.57 KB)
Censor, Y, Gibali, A, Lenzen, F and Schnörr, C (2016). The Implicit Convex Feasibility Problem and Its Application to Adaptive Image Denoising. J. Comp. Math. 34 608-623
Biller, A, Badde, S, Nagel, A, Neumann, J O, Wick, W, Hertenstein, A, Bendszus, M, Sahm, F, Benkhedah, N and Kleesiek, J (2016). Improved Brain Tumor Classification by Sodium MR Imaging: Prediction of IDH Mutation Status and Tumor Progression. American Journal of Neuroradiology. 37 66-73
Sanakoyeu, A, Ma, P, Tschernezki, V and Ommer, B (2021). Improving Deep Metric Learning by Divide and Conquer. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). https://arxiv.org/abs/2109.04003
Kiefhaber, D, Zappa, C J and Jähne, B (2015). Influence of natural surfactants on short wind waves in the coastal Peruvian waters. 12 1291–1325
Suhr, H, Wehnert, G, Schneider, K, Bittner, C, Scholz, T, Geißler, P, Jähne, B and Scheper, T (1995). In-situ microscopy for on-line characterization of cell-populations in bioreactors, including concentration measurements by depth from focus. Biotechnology and Bioengineering. 47 106--116
Wolf, S, Hamprecht, F A and Funke, J (2020). Instance Separation Emerges from Inpainting. arXiv preprint arXiv:2003.00891
Schütz, L M, Louveaux, M, Vilches-Barro, A, Bouziri, S, Cerrone, L, Wolny, A, Kreshuk, A, Hamprecht, F A and Maizel, A (2021). Integration of Cell Growth and Asymmetric Division during Lateral Root Initiation in Arabidopsis thaliana. Plant and Cell Physiology. 62 1269-1279
Gall, J, Potthoff, J, Schnörr, C, Rosenhahn, B and Seidel, H - P (2007). Interacting and Annealing Particle Filters: Mathematics and a Recipe for Applications. J.~Math.~Imag.~Vision. 28 1--18PDF icon Technical Report (1.11 MB)
Gall, J, Potthoff, J, Schnörr, C, Rosenhahn, B and Seidel, H - P (2007). Interacting and Annealing Particle Filters: Mathematics and a Recipe for Applications. J. Math. Imag. Vision. 28 1–18
Rother, C and Kolmogorov, V (2011). Interactive foreground extraction using graph cut. Advances in Markov \ldots. 1–20. http://research.microsoft.com/pubs/147408/rotheretalmrfbook-grabcut.pdf
Ding, L and Yilmaz, A (2010). Interactive image segmentation using probabilistic hypergraphs. Pattern Recognition. 43 1863–1873. http://www.research.microsoft.com/vision/cambridge
Wenig, M, Spichtinger, N, Stohl, A, Held, G, Beirle, S, Wagner, T, Jähne, B and Platt, U (2003). Intercontinental transport of nitrogen oxide pollution plumes. Atmos. Chem. Phys. 3 387--393
Wenig, M, Spichtinger, N, Stohl, A, Held, G, Beirle, S, Wagner, T, Jähne, B and Platt, U (2002). Intercontinental transport of nitrogen oxide pollution plumes. acpd. 3 2151--2165
Kunz, J and Jähne, B (2018). Investigating small scale air-sea exchange processes via thermography. Front. Mech. Eng. 26
Friman, S I and Jähne, B (2019). Investigating SO2 transfer across the air–water interface via LIF. Exp. Fluids. 60 65
Jähne, B, Libner, P, Fischer, R, Billen, T and Plate, E J (1989). Investigating the transfer process across the free aqueous boundary layer by the controlled flux method. Tellus. 41B 177--195
Schimpf, U, Garbe, C S and Jähne, B (2004). Investigation of transport processes across the sea surface microlayer by infrared imagery. J. Geophys. Res. 109 C08S13
Broecker, W S, Ledwell, J R, Takahashi, T, Weiss, R, Merlivat, L, Memery, L, Jähne, B and Münnich, K O (1986). Isotopic versus micrometeorologic ocean CO$_2$ fluxes: A serious conflict. J. Geophys. Res. 91 10517--10528
Stefanoiu, A, Weinmann, A, Storath, M, Navab, N and Baust, M (2016). Joint Segmentation and Shape Regularization with a Generalized Forward Backward Algorithm. IEEE Transactions on Image Processing. 25 3384 - 3394PDF icon Technical Report (3.55 MB)
Diego, F, Serrat, J and López, A M (2012). Joint SpatioTemporal Alignment of Sequences. IEEE Transactions on Multimedia (TMM). PP (99) 1PDF icon Technical Report (5.15 MB)
Storath, M, Weinmann, A and Unser, M (2017). Jump-penalized least absolute values estimation of scalar or circle-valued signals. Information and Inference. 6 225–245PDF icon Technical Report (3.4 MB)
Fiaschi, L, Grosser, K - H, Afonso, B, Zlatic, M and Hamprecht, F A (2013). Keeping Count: Leveraging Temporal Context to Count Heavily Overlapping Objects. ISBI 2013.Proceedings. 656-659PDF icon Technical Report (711.68 KB)
Andres, B, Kappes, J H, Köthe, U and Hamprecht, F A (2010). The Lazy Flipper: MAP Inference in Higher-Order Graphical Models by Depth-limited Exhaustive Search. ArXiv e-prints. http://arxiv.org/abs/1009.4102PDF icon Technical Report (625.06 KB)
Hühnerbein, R, Savarino, F, Petra, S and Schnörr, C (2019). Learning Adaptive Regularization for Image Labeling Using Geometric Assignment. preprint: arXiv. https://arxiv.org/abs/1910.09976
Nickisch, H, Rother, C, Kohli, P and Rhemann, C (2010). Learning an Interactive Segmentation System - Supplemental Material
Heiler, M and Schnörr, C (2006). Learning Sparse Representations by Non-Negative Matrix Factorization and Sequential Cone Programming. J. Mach. Learning Res. 7 1385–1407. http://www.cvgpr.uni-mannheim.de/Publications
Ommer, B and Buhmann, J M (2010). Learning the Compositional Nature of Visual Object Categories for Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence. IEEE. 32 501--516PDF icon Technical Report (2.78 MB)
Fiaschi, L, Nair, R, Köthe, U and Hamprecht, F A (2012). Learning to Count with Regression Forest and Structured Labels. ICPR 2012. Proceedings. 2685-2688PDF icon Technical Report (3.66 MB)

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