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Ommer, B and Buhmann, J M (2005). Object Categorization by Compositional Graphical Models. Proceedings of the International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition. Springer. 3757 235--250

Technical Report (2.07 MB)

Vicente, S, Rother, C and Kolmogorov, V (2011). Object cosegmentation. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2217–2224

Zheng, S, Prisacariu, V Adrian, Averkiou, M, Cheng, M Ming, Mitra, N J, Shotton, J, Torr, P H S and Rother, C (2015). Object proposals estimation in depth image using compact 3D shape manifolds. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 9358 196–208

Schmitzer, B and Schnörr, C (2013). Object Segmentation by Shape Matching with Wasserstein Modes. Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR 2013). 123-136

Bleyer, M, Rother, C, Kohli, P, Scharstein, D and Sinha, S (2011). Object stereo Joint stereo matching and object segmentation. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 3081–3088

Ulman, V, Maška, M, Magnusson, K E G, Ronneberger, O, Haubold, C, Harder, N, Matula, P, Matula, P, Svoboda, D, Radojevic, M, Smal, I, Rohr, K, Jaldén, J, Blau, H M, Dzyubachyk, O, Lelieveldt, B, Xiao, P, Li, Y, Cho, S - Y, Dufour, A, Olivo-Marin, J C, Reyes-Aldasoro, C C, Solis-Lemus, J A, Bensch, R, Brox, T, Stegmaier, J, Mikut, R, Wolf, S, Hamprecht, F A, Esteves, T, Quelhas, P, Demirel, Ö, Malström, L, Jug, F, Tomančák, P, Meijering, E, Muñoz-Barrutia, A, Kozubek, M and Ortiz-de-Solorzano, C (2017). An Objective Comparison of Cell Tracking Algorithms. Nature Methods. 14 1141-1152

Technical Report (4.24 MB)

Kaster, F O, Kassemeyer, S, Merkel, B, Nix, O and Hamprecht, F A (2010). An object-oriented library for systematic training and comparison of classifiers for computer-assisted tumor diagnosis from MRSI measurements. Bildverarbeitung für die Medizin 2010 -- Algorithmen, Systeme, Anwendungen. Springer. 97-101

Technical Report (1.12 MB)

Kaster, F O, Merkel, B, Nix, O and Hamprecht, F A (2011). An object-oriented library for systematic training and comparison of classifiers for computer-assisted tumor diagnosis from MRSI measurements. Computer Science - Research and Development. 26 65-85

Technical Report (808.16 KB)

Mann, S (1998). Objektbasierte Bildfolgenanalyse Zur Bewegungsbestimmung Im In Vitro Motility Assay Unter Verwendung Eines Strukturtensorverfahrens. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg

Jähne, (2009). Objektive Kriterien unterstützen die anwendungsorientierte Auswahl einer Kamera. http://www.vdma-verlag.com/home/p464.html

Küsters, (2001). Objektverfolgung Und Bildfusion Zur Untersuchung Wachsender Pflanzenwurzeln. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg

Menze, B H, Kelm, B Michael, Splitthoff, N, Köthe, U and Hamprecht, F A (2011). On oblique random forests. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2011. Proceedings. Springer. 453-469

Technical Report (665.33 KB)

Schimpf, U, Frew, N M, Kalkenings, R, Garbe, C S and Jähne, B (2003). Observational studies of parameters influencing air--sea gas exchange. Geophysical Research Abstracts. 5 09328

Klinke, J, Jähne, B and Long, S R (1999). Observations of free and bound gravity-capillary Waves. The Wind-Driven Air-Sea Interface, Electromagnetic and Acoustic Sensing, Wave Dynamics and Turbulent Fluxes. 87--88

Jähne, (2015). The ocean in the lab: measurements with light and shadow. Ruperto Carola Forschungsmagazin Heidelberg University. 7 52–59

Huang, N E, Toba, Y, Shen, Z, Klinke, J, Jähne, B and Banner, M L (2001). Ocean wave spectra and integral properties. Wind Stress over the Ocean. Cambridge University Press. 82--123

Takami, M, Bell, P and Ommer, B (2014). Offline Learning of Prototypical Negatives for Efficient Online Exemplar SVM. Winter Conference on Applications of Computer Vision. IEEE. 377--384. http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6836075

Griessinger, M (2008). Oject Detection With Generic Features: An Application To Sted Microscopy. University of Heidelberg

Horvát, E - A, Hanselmann, M, Hamprecht, F A and Zweig, K A (2012). One plus one makes three (for social networks). PLoS ONE. 4,7

Geißler, P and Jähne, B (1995). One-image depth-from-focus for concentration measurements. Proc. ISPRS Intercommission Workshop `From Pixels to Sequences', Zurich, March 22 - 24, 1995, In Int'l Arch. of Photog. and Rem. Sens. RISC Books. XXX-5W1 122--127

Ruhnau, P, Stahl, A and Schnörr, C (2006). On-Line Variational Estimation of Dynamical Fluid Flows with Physics-Based Spatio-Temporal Regularization. Proc.~DAGM 2006. Springer. 375-388 375-388

Technical Report (902.47 KB)

Ruhnau, P, Stahl, A and Schnörr, C (2006). On-Line Variational Estimation of Dynamical Fluid Flows with Physics-Based Spatio-Temporal Regularization. Proc. DAGM 2006. Springer. 375-388 375-388

Andres, B, Beier, T and Kappes, J H (2012). OpenGM: A C++ Library for Discrete Graphical Models. ArXiv e-prints

Wenig, M, Jähne, B and Platt, U (2005). Operator representation as a new differential optical absorption spectroscopy formalism. Appl. Optics. 44 3246-3253

Barron, J L, Liptay, A and Spies, H (2000). Optical and range flow to measure 3D plant growth and motion. Image Vision Computing New Zealand. 68--77

Becker, F, Petra, S and Schnörr, C (2014). Optical Flow. Handbook of Mathematical Methods in Imaging. Springer

Garbe, C S, Roetmann, K and Jähne, B (2006). An optical flow based technique for the non-invasive measurement of microfluidic flows. 12th Intern. Symp. on Flow Visualization, Göttingen, 10--14. September 2006

Garbe, C S, Roetmann, K, Beushausen, V and Jähne, B (2008). An optical flow MTV based technique for measuring microfluidic flow in the presence of diffusion and Taylor dispersion. Exp. Fluids. 44 439--450

Schmund, D, Schurr, U and Jähne, B (2000). Optical leaf growth analysis. Computer Vision and Applications - A Guide for Students and Practitioners. Academic Press. 640-641

Kiefhaber, D (2014). Optical Measurement of Short Wind Waves --- from the Laboratory to the Field. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg. Dissertation. http://www.ub.uni-heidelberg.de/archiv/16304

Kiefhaber, D, Rocholz, R, Bauer, P Salomon and Jähne, B (2013). Optical measurement of surface ocean waves. 3rd EOS Topical Meeting on Blue Photonics --- Optics in the Sea

Mischler, W and Jähne, B (2012). Optical measurements of bubbles and spray in wind/water facilities at high wind speeds. 12th International Triennial Conference on Liquid Atomization and Spray Systems 2012, Heidelberg (ICLASS 2012)

Klinke, J (1996). Optical Measurements of Small-Scale Wind Generated Water Surface Waves in the Laboratory and the Field. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg

Jähne, B and Jähne, B (1989). Optical measuring technique for small scale water surface waves. Advanced Optical Instrumentation for Remote Sensing of the Earth's Surface from Space, SPIE Proceeding 1129, International Congress on Optical Science and Engineering, Paris, 24-28 April 1989. 147--152

Mischler, W, Rocholz, R and Jähne, B (2009). Optical method for measuring size-distribution and lifetime of bubbles. Poster abstracts SOLAS Open Science Conference, Barcelona, 16--19 Sep. 2009

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