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Klinke, J and Jähne, B (1996). Wave number spectra of short wind waves: implications from laboratory studies. Proc.\ The Air-Sea Interface, Radio and Acoustic Sensing, Turbulence and Wave Dynamics, Marseille, 24--30. June 1993. RSMAS, University of Miami. 367--372
Klinke, J, Kudryavtsev, V N, Makin, V K and Jähne, B (2001). Wavenumber Spectra of Short Wind Waves: Laboratory Measurements and Interpretation. IGARSS '01, Geoscience and Remote Sensing Symposium, Sydney, NSW, Australia. 2 965-967
Schmitzer, B and Schnörr, C (2012). Weakly Convex Coupling Continuous Cuts and Shape Priors. Scale Space and Variational Methods (SSVM 2011). 423-434
Haußmann, (2016). Weakly Supervised Detection With Gaussian Processes. University of Heidelberg
Nguyen, M Hoai, Torresani, L, De La Torre, F and Rother, C (2009). Weakly supervised discriminative localization and classification: A joint learning process. Proceedings of the IEEE International Conference on Computer Vision. 1925–1932
Nguyen, M Hoai, Torresani, L, De La Torre, F and Rother, C (2009). Weakly supervised discriminative localization and classification: A joint learning process. Proceedings of the IEEE International Conference on Computer Vision. 1925–1932
Xu, B (2013). Weakly Supervised Learning: Active Schemes And Partial Annotations. University of Heidelberg
Jäger, M, Knoll, C and Hamprecht, F A (2008). Weakly Supervised Learning of a Classifier for Unusual Event Detection. IEEE Transactions on Image Processing. 17 1700-1708PDF icon Technical Report (295.32 KB)
Ufer, N, Lui, K To, Schwarz, K, Warkentin, P and Ommer, B (2019). Weakly Supervised Learning of Dense SemanticCorrespondences and Segmentation. German Conference on Pattern Recognition (GCPR)PDF icon article (6.1 MB)
Straehle, C N, Köthe, U and Hamprecht, F A (2013). Weakly supervised learning of image partitioning using decision trees with structured split criteria. ICCV 2013. Proceedings. 1849-1856PDF icon Technical Report (5.97 MB)
Pandey, N (2019). Weakly Supervised Semantic Segmentation. Heidelberg University
Platt, T (2011). Weiterentwicklung Einer Hochauflösenden Lif-Methode Zur Messung Von Sauerstoffkonzentrationsprofilen In Der Wasserseitigen Grenzschicht. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg
Jähne, B, Köhler, H - J, Rath, R and Wierzimok, D (1993). Wellenamplitudenmessungen mittels videometrischer Bildverarbeitung. Mitteilungsblatt der Bundesanstalt für Wasserbau. 70 27--62
Jähne, B, Balschbach, G and Fuß, D (2002). Wellenbewegte Wasseroberfläche. Nahbereichsphotogrammetrie in der Praxis, Beispiele und Problemlösungen. Wichmann. 259--262. http://d-nb.info/96618503X
Jähne, (1999). Wenn Unsichtbares sichtbar wird
Köthe, (2008). What Can We Learn from Discrete Images about the Continuous World. Discrete Geometry for Computer Imagery. Springer. 4992 4-19
Jähne, (2020). What controls air-sea gas exchange at extreme wind speeds? Evidence from laboratory experiments. Recent Advances in the Study of Oceanic Whitecaps. Springer. 133–150
Meister, S, Izadi, S, Kohli, P, Hämmerle, M, Rother, C and Kondermann, D (2012). When Can We Use KinectFusion for Ground Truth Acquisition?. Workshop on Color-Depth Camera Fusion in Robotics, IEEE International Conference on Intelligent Robots and Systems
Meister, S, Izadi, S, Kohli, P and M Hämmerle, M \ (2012). When can we use KinectFusion for ground truth acquisition?. Proc Workshop on \ldots. 3–8. http://meshlab.sourceforge.net/ http://www.msr-waypoint.net/en-us/um/people/pkohli/papers/mikhrk_iros_dataset_2012.pdf%5Cnpapers3://publication/uuid/2615CF9D-C632-4E39-B1C4-B32A4A5D339C
Márquez-Valle, P, Gil, D, Hernàndez-Sabaté, A and Kondermann, D (2013). When is a confidence measure good enough?. submitted to CVPR 2013
Renard, B Y, Kirchner, M, Monigatti, F, Ivanov, A R, Rappsilber, J, Winter, D, Steen, J A J, Hamprecht, F A and Steen, H (2009). When Less Can Yield More - Computational Preprocessing of MS/MS Spectra for Peptide Identification Preprocessing. Proteomics. 9 4978-4984PDF icon Technical Report (901.78 KB)
Jähne, (1999). When the invisible becomes visible. German research, Magazine of the German Research Foundation (DFG). 30--33
Kreshuk, A, Funke, J, Cardona, A and Hamprecht, F A (2015). Who is talking to whom: synaptic partner detection in anisotropic volumes of insect brain. MICCAI. Proceedings. Springer. LNCS 9349 661-668PDF icon Technical Report (2.14 MB)
Esparza, J, Helmle, M and Jähne, B (2014). Wide base stereo with fisheye optics: a robust approach for 3D reconstruction in driving assistance. Pattern Recognition, 36th German Conference, GCPR 2014, Münster, Germany, September 2-5, 2014. Springer. 8753 342--353
Liefermann, A, Ramamonjiarisoa, A and Jähne, B (1985). Wind tunnel investigation of the characterization of radar backscattering by different wave fields. Third International Colloquium Spectral Signatures of Objects in Remote Sensing. 1 137--140. http://adsabs.harvard.edu/abs/1985ssor.proc.137L
Jähne, B, Huber, W A, Dutzi, A, Wais, T and Ilmberger, J (1984). Wind/wave-tunnel experiments on the Schmidt number and wave field dependence of air-water gas exchange. Gas transfer at water surfaces. Reidel. 303--309
Jähne, B, Degreif, K and Kuss, J (2010). Wind/wave-tunnel measurements of chemical enhancement of the carbon dioxide gas exchange rate. 6th Int. Symp. Gas Transfer at Water Surfaces, Kyoto, May 17--21, 2010
Wenig, M (1998). Wolkenklassifizierung Mittels Bildsequenzanalyse Auf Gome-Satellitendaten. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg
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Blum, O, Brattoli, B and Ommer, B (2018). X-GAN: Improving Generative Adversarial Networks with ConveX Combinations. German Conference on Pattern Recognition (GCPR) (Oral). Stuttgart, GermanyPDF icon Article (6.65 MB)PDF icon Supplementary material (7.96 MB)PDF icon Oral slides (14.96 MB)

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