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(2000). Künstliche Intelligenz: Special Issue on Medical Computer Vision. 3

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Geißler, P and Jähne, B (1997). Laboratory and inshore measurements of bubble size distributions. Proc. Natural Physical Processes associated with Sea Surface Sound, Southampton, July 21--24, 1997. 147--154

Krall, K E (2013). Laboratory Investigations of Air-Sea Gas Transfer under a Wide Range of Water Surface Conditions. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg. Dissertation. http://www.ub.uni-heidelberg.de/archiv/14392

Friman, S (2020). Laboratory investigations of concentration and wind profiles close to the wind-driven wavy water surface. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ. Heidelberg, Heidelberg. Dissertation

Beyer, M, Jähne, B and Melville, W K (1994). Laboratory studies of long-wave/short-wave interaction using wavelet analysis of space-time images. Proc. 2nd Inter. Conf. on Air-Sea Interaction and on Meteorology and Oceanography of the Coastal Zone, Lisbon, 22.--27. September 1994

Richter, K E and Jähne, B (2011). A laboratory study of the Schmidt number dependency of air-water gas transfer. Gas Transfer at Water Surfaces 2010. 322--332. http://hdl.handle.net/2433/156156

Hering, F (1996). Lagrangesche Untersuchungen des Strömungsfeldes unterhalb der wellenbewegten Wasseroberfläche mittels Bildfolgenanalyse. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg

Walecki, R (2013). Large-Scale Automatic Reconstruction Of Myelianated Axons And Detection Of The Nodes Of Ranvier. University of Heidelberg

Andres, B, Kappes, J H, Beier, T, Köthe, U and Hamprecht, F A (2012). The Lazy Flipper: Efficient Depth-Limited Exhaustive Search in Discrete Graphical Models. Computer Vision - {ECCV} 2012 - 12th European Conference on Computer Vision, Florence, Italy, October 7-13, 2012, Proceedings, Part {VII}. http://dx.doi.org/10.1007/978-3-642-33786-4_12

Technical Report (446.28 KB)

Andres, B, Kappes, J H, Beier, T, Köthe, U and Hamprecht, F A (2012). The Lazy Flipper: Efficient Depth-limited Exhaustive Search in Discrete Graphical Models. ECCV 2012

Technical Report (532.64 KB)

Andres, B, Kappes, J Hendrik, Beier, T, Köthe, U and Hamprecht, F A (2012). The Lazy Flipper: Efficient Depth-limited Exhaustive Search in Discrete Graphical Models. ECCV 2012

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/1009.4102

Technical Report (625.06 KB)

Schimmel, F (2018). Learnability Of Approximated Graph Cut Segmentation. Heidelberg University

Schott, L (2017). Learned Watershed Algorithm: End-To-End Learning Of Seeded Segmentation. Heidelberg University

Wolf, S, Schott, L, Köthe, U and Hamprecht, F A (2017). Learned Watershed: End-to-End Learning of Seeded Segmentation. ICCV. 2030-2038

Technical Report (3.76 MB)

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

Hühnerbein, R, Savarino, F, Petra, S and Schnörr, C (2019). Learning Adaptive Regularization for Image Labeling Using Geometric Assignment. Proc. SSVM. Springer

Withopf, D and Jähne, B (2006). Learning algorithm for real-time vehicle tracking. Proc. IEEE Intelligent Transportation Systems Conference ITSC '06. 516--521

Nickisch, H, Rother, C, Kohli, P and Rhemann, C (2010). Learning an Interactive Segmentation System - Supplemental Material

Krull, A, Brachmann, E, Michel, F, Yang, M Ying, Gumhold, S and Rother, C (2015). Learning analysis-by-synthesis for 6d pose estimation in RGB-D images. Proceedings of the IEEE International Conference on Computer Vision. 2015 Inter 954–962

Fiaschi, L (2013). Learning Based Biological Image Analysis. University of Heidelberg

Ommer, B and Buhmann, J M (2006). Learning Compositional Categorization Models. Proceedings of the European Conference on Computer Vision. Springer. 3953 316--329

Technical Report (1.35 MB)

Jancsary, J, Nowozin, S and Rother, C (2013). Learning convex QP relaxations for structured prediction. 30th International Conference on Machine Learning, ICML 2013. 1952–1960

Yarlagadda, P, Eigenstetter, A and Ommer, B (2012). Learning Discriminative Chamfer Regularization. BMVC. Springer. 1--11. http://www.bmva.org/bmvc/2012/BMVC/paper020/paper020.pdf

Hoai, M, Torresani, L, De La Torre, F and Rother, C (2014). Learning discriminative localization from weakly labeled data. Pattern Recognition. 47 1523–1534

Schiegg, M, Diego, F and Hamprecht, F A (2016). Learning Diverse Models: The Coulomb Structured Support Vector Machine. ECCV. Proceedings. Springer. LNCS 9907 585-599

Technical Report (2.54 MB)

Antic, B and Ommer, B (2014). Learning Latent Constituents for Recognition of Group Activities in Video. Proceedings of the European Conference on Computer Vision (ECCV) (Oral). Springer. 33--47

Technical Report (4.54 MB)

Brachmann, E and Rother, C (2018). Learning Less is More - 6D Camera Localization via 3D Surface Regression. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 4654–4662. http://arxiv.org/abs/1711.10228

Diego, F and Hamprecht, F A (2013). Learning Multi-Level Sparse Representation. NIPS. Proceedings. http://papers.nips.cc/paper/5076-learning-multi-level-sparse-representations

Technical Report (2.79 MB)

Diego, F and Hamprecht, F A (2013). Learning Multi-Level Sparse Representation for Identifying Neuronal Activity. Signal Processing with Adaptive Sparse Structured Representations Workshop (SPARS). Book of Abstracts

Technical Report (1.05 MB)

Afifi, M, Derpanis, K G, Ommer, B and Brown, M S (2021). Learning Multi-Scale Photo Exposure Correction. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). https://arxiv.org/abs/2003.11596

Bergtholdt, M, Kappes, J H and Schnörr, C (2006). Learning of Graphical Models and Efficient Inference for Object Class Recognition. Proc. DAGM 2006. Springer. 375-388 375-388

Jehle, M, Sommer, C and Jähne, B (2010). Learning of Optimal Illumination for Material Classification. Proceedings of the 32nd DAGM Symposium on Pattern Recognition, Darmstadt, Germany. Springer. 563-572

Jehle, M, Sommer, C and Jähne, B (2010). Learning of optimal illumination for material classification. Pattern Recognition. Springer. 6376 563--572

Heiler, M and Schnörr, C (2005). Learning Sparse Image Codes by Convex Programming. Proc. Tenth IEEE Int. Conf. Computer Vision (ICCV'05). Beijing, China. 1667-1674

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