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J. H. Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Sungwoong, K., Kausler, B. X., Lellmann, J., Komodakis, N., and Rother, C., “A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problems”, in CVPR 2013. Proceedings, 2013.

Technical Report (1.35 MB)

R. Szeliski, Zabih, R., Scharstein, D., Veksler, O., Kolmogorov, V., Agarwala, A., Tappen, M., and Rother, C., “A comparative study of energy minimization methods for Markov random fields with smoothness-based priors”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 30, pp. 1068–1080, 2008.

R. Szeliski, Zabih, R., Scharstein, D., Veksler, O., Kolmogorov, V., Agarwala, A., Tappen, M., and Rother, C., “A comparative study of energy minimization methods for Markov random fields with smoothness-based priors”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 30, pp. 1068–1080, 2008.

C. Kräuter, Richter, K. E., Jähne, B., Mesarchaki, E., and Williams, J., “A comparative lab study of tansfer velocities of volatile tracers with widely varying solubilities”, in DPG Frühjahrstagung Dresden, Fachverband Umweltphysik, 2011.

L. Nagel, Krall, K. Ellen, and Jähne, B., “Comparative heat and gas exchange measurements in the Heidelberg Aeolotron, a large annular wind-wave tank”, Ocean Sci., vol. 11, p. 111--120, 2015.

L. Nagel, Krall, K. Ellen, and Jähne, B., “Comparative heat and gas exchange measurements in the Heidelberg Aeolotron, a large annular wind-wave tank”, Ocean Sci. Discuss., vol. 11, p. 1691--1718, 2014.

B. Jähne, “A comparative analytical study of low-level motion estimators in space-time images”, in Proc. 16. DAGM-Symposium Mustererkennung, 1994.

A. Bruhn, Weickert, J., and Schnörr, C., “Combining the Advantages of Local and Global Optic Flow Methods”, in Pattern Recognition, Proc. 24th DAGM Symposium, Zürich, Switzerland, 2002, vol. 2449, pp. 454–462.

B. Michael Kelm, Pal, C., and McCallum, A., “Combining Generative and Discriminative Methods for Pixel Classification with Multi-Conditional Learning.”, in ICPR 2006, 2006, vol. 2, pp. 828-832.

Technical Report (114.99 KB)

F. Hering, Wierzimok, D., Melville, W. K., and Jähne, B., “Combined wave and flow field visualization for investigation of short-wave/long-wave interaction”, in Proc.\ The Air-Sea Interface, Radio and Acoustic Sensing, Turbulence and Wave Dynamics, Marseille, 24--30. June 1993, 1996, p. 133--138.

R. Rocholz, Wanner, S., Schimpf, U., and Jähne, B., “Combined visualization of wind waves and water surface temperature”, in Gas Transfer at Water Surfaces 2010, 2011, p. 496--506.

M. Baust, Weinmann, A., Wieczorek, M., Lasser, T., Storath, M., and Navab, N., “Combined Tensor Fitting and TV Regularization in Diffusion Tensor Imaging based on a Riemannian Manifold Approach”, IEEE Transactions on Medical Imaging, vol. 35, no. 8, pp. 1972–1989, 2016.

Technical Report (8.65 MB)

J. Neumann, Schnörr, C., and Steidl, G., “Combined SVM-based Feature Selection and Classification”, Machine Learning, vol. 61, pp. 129-150, 2005.

S. Waas and Jähne, B., “Combined slope-height measurements of short wind waves: first results from field and laboratory measurements”, in Optics of the Air-Sea Interface: Theory and Measurements, 1992, vol. 1749, p. 295--306.

B. Jähne, Schmidt, M., and Rocholz, R., “Combined optical slope/height measurements of short wind waves: principles and calibration”, Meas. Sci. Technol., vol. 16, p. 1937--1944, 2005.

S. Waas and Jähne, B., “Combined height/slope/curvature measurements of short ocean wind waves”, in Proc.\ The Air-Sea Interface, Radio and Acoustic Sensing, Turbulence and Wave Dynamics, Marseille, 24--30. June 1993, 1996, p. 383--388.

S. Waas and Jähne, B., “Combined height/slope/curvature measurements of short ocean wind waves”. 1994.

M. F. Carlsohn, Menze, B. H., Kelm, B. Michael, Hamprecht, F. A., Kercek, A., Leitner, R., and Polder, G., “Color image processing”, vol. 7(17), R. Lukac and Plataniotis, K. N., Eds. CRC Press, 2006, pp. 393-419.

D. Breitenreicher, Lellmann, J., and Schnörr, C., “COAL: a generic modelling and prototyping framework for convex optimization problems of variational image analysis”, Optimization Methods and Software, vol. 28, pp. 1081-1094, 2013.

Technical Report (1.69 MB)

M. Geese, Jähne, B., and Ruhnau, P., “CNN Based Dark Signal Non-Uniformity Estimation”, CNNA, pp. 1-6, 2012.

M. Geese, Ruhnau, P., and Jähne, B., “CNN based dark signal non-uniformity estimation”, in Cellular Nanoscale Networks and Their Applications (CNNA), 2012 13th International Workshop on, 2012, p. 1--6.

A. Kannan, Winn, J., and Rother, C., “Clustering appearance and shape by learning jigsaws”, in Advances in Neural Information Processing Systems, 2007, pp. 657–664.

A. Kannan, Winn, J., and Rother, C., “Clustering appearance and shape by learning jigsaws”, in Advances in Neural Information Processing Systems, 2007, pp. 657–664.

M. Brosowsky, “Cluster Resolving for Animal Tracking: Multi Hypotheses Tracking with Part Based Model for Object Hypotheses Generation and Pose Estimation”, University of Heidelberg, 2017.

M. Wenig, Leue, C., Platt, U., Jähne, B., and Haußecker, H., “Cloud classification analyzing image sequences”, Computer Vision and Applications. A Guide for Students and Practitioners. Academic Press, p. 652--653, 2000.

S. R. Long and Klinke, J., “A closer look at short waves generated by wave interactions with adverse currents”, in Gas Transfer at Water Surfaces, 2002, vol. 127, p. 121--128.

M. Bautista, Sanakoyeu, A., Sutter, E., and Ommer, B., “CliqueCNN: Deep Unsupervised Exemplar Learning”, in Proceedings of the Conference on Advances in Neural Information Processing Systems (NIPS), Barcelona, 2016.

Article (5.79 MB)

F. O. Kaster, Kelm, B. Michael, Zechmann, C. M., Weber, M. - A., Hamprecht, F. A., and Nix, O., “Classification of Spectroscopic Images in the DIROlab Environment”, in World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany, 2009, vol. 25/V, p. 252--255.

Technical Report (145.73 KB)

B. H. Menze and Ur, J. A., “Classification of multispectral ASTER imagery in the archaeological survey for settlement sites of the Near East”, in Proc 10th International Symposium on Physical Measurements and Signature in Remote Sensing (ISPMRS 07), Davos, Switzerland, 2007.

Technical Report (920.71 KB)

B. H. Menze, Wormit, M., Bachert, P., Lichy, M. P., Schlemmer, H. - P., and Hamprecht, F. A., “Classification of in vivo magnetic resonance spectra”, in Classification in ubiquitous challenge: Proceedings of the GfKl 2004, 2004, pp. 362-369.

Technical Report (240.1 KB)

F. A. Hamprecht, “Classification”, Practical Handbook on Image Processing for Scientific and Technical Applications. CRC Press, pp. 509-519, 2004.

Technical Report (320.84 KB)

F. Lenzen, Becker, F., Lellmann, J., Petra, S., and Schnörr, C., “A Class of Quasi-Variational Inequalities for Adaptive Image Denoising and Decomposition”, Computational Optimization and Applications (COAP), vol. 54 (2), pp. 371-398, 2013.

F. Lenzen, Becker, F., Lellmann, J., Petra, S., and Schnörr, C., “A class of quasi-variational inequalities for adaptive image denoising and decomposition”, Computational Optimization and Applications, vol. 54, pp. 371-398, 2013.

Technical Report (748.66 KB)

J. Heers, Schnörr, C., and Stiehl, H. S., “A class of parallel algorithms for nonlinear variational image segmentation”, in Proc. Noblesse Workshop on Non–Linear Model Based Image Analysis (NMBIA'98), Glasgow, Scotland, 1998.

B. Michael Kelm, Menze, B. H., Neff, T., Zechmann, C. M., and Hamprecht, F. A., “CLARET: a tool for fully automated evaluation of MRSI with pattern recognition methods.”, in Bildverarbeitung für die Medizin 2006 - Algorithmen, Systeme, Anwendungen, 2006, pp. 51-55.

Technical Report (275.25 KB)

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