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

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