Publications

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P. Bell and Ommer, B., Computer Vision und Kunstgeschichte — Dialog zweier Bildwissenschaften, in Computing Art Reader: Einführung in die digitale Kunstgeschichte, P. Kuroczyński et al. (ed.), 2018.PDF icon 413-17-83318-2-10-20181210.pdf (2.98 MB)
B. Jähne and Haußecker, H., Computer Vision and Applications: A Guide for Students and Practitioners. Academic Press, 2000, p. 679.
M. Wulf, Stiehl, H. S., and Schnörr, C., On the computational rôle of the primate retina, in Proc. 2nd ICSC Symposium on Neural Computation (NC 2000), Berlin, Germany, 2000.
M. Kirchner, Renard, B. Y., Köthe, U., Pappin, D. J., Hamprecht, F. A., Steen, J. A. J., and Steen, H., Computational Protein Profile Similarity Screening for Quantitative Mass Spectrometry Experiments, Bioinformatics, vol. 26 (1), pp. 77-83, 2010.PDF icon Technical Report (380.19 KB)
M. Hanselmann, Computational Methods for the Analysis of Mass Spectrometry Images. University of Heidelberg, 2010.
F. Rathke and Schnörr, C., A Computational Approach to Log-Concave Density Estimation, An. St. Univ. Ovidius Constanta, vol. 23, pp. 151-166, 2015.PDF icon Technical Report (1.07 MB)
F. Rathke and Schnörr, C., A Computational Approach to Log-Concave Density Estimation, An. St. Univ. Ovidius Constanta, vol. 23, pp. 151-166, 2015.
S. V. E. Keränen, DePace, A., Hendriks, C. L. Luengo, Fowlkes, C., Arbelaez, P., Ommer, B., Brox, T., Henriquez, C., Wunderlich, Z., Eckenrode, K., Fischer, B., Hammonds, A., and Celniker, S. E., Computational Analysis of Quantitative Changes in Gene Expression and Embryo Morphology between Species, in Evolution-The Molecular Landscape, 2009.
C. Schnörr, Computation of Discontinuous Optical Flow by Domain Decomposition and Shape Optimization, ijcv, vol. 8, pp. 153–165, 1992.
C. Schnörr, Computation of Discontinuous Optical Flow by Domain Decomposition and Shape Optimization, in Proc. British Machine Vision Conference, Oxford/UK, 1990, pp. 109–114.
R. Dalitz, Petra, S., and Schnörr, C., Compressed Motion Sensing, in Proc. SSVM, 2017, vol. 10302.
F. Hering, Haußecker, H., Dieter, J., Netzsch, T., and Jähne, B., A comprehensive study of algorithms for multidimensional flow field diagnostics, in Proc. Optical 3D Measurement Techniques IV, Zurich, Sept. 29 - Oct. 2, 1997, 1997, p. 436--443.
B. Ommer and Buhmann, J. M., A Compositionality Architecture for Perceptual Feature Grouping, in Proceedings of the International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition, 2003, vol. 2683, p. 275--290.PDF icon Technical Report (2.89 MB)
B. Ommer and Buhmann, J. M., Compositional Object Recognition, Segmentation, and Tracking in Video, in Proceedings of the International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition, 2007, vol. 4679, p. 318--333.PDF icon Technical Report (2.78 MB)
B. Jähne, Complex Motion, Proceedings of the 1st Workshop, Günzburg, October 2004, vol. 3417. Springer, 2007.
B. Jähne and Jähne, B., Complex motion in environmental physics and live sciences, Complex Motion, vol. 3417. Springer, p. 92--105, 2007.
D. van Halsema, Calkoen, C. J., Oost, W. A., Snoeij, P., and Jähne, B., Comparisons of X-band Radar Backscatter Measurements with Area extended wave slop measurements made in a large Wind/Wave Tank, in Proc. IGARSS'89, 1989, vol. 5, p. 2997--3001.
D. van Halsema, Calkoen, C. J., Oost, W. A., Snoeij, P., Vogelzang, J., and Jähne, B., Comparisons of backscattering calculations with measurements made in a large wind/wave flume, in Proc. IGARSS'92, 1992, vol. 2, p. 1451--1453.
A. Haja, Abraham, S., and Jähne, B., A Comparison of Region Detectors for Tracking, in Pattern Recognition, Proceedings 30th DAGM Symposium, Munich, Germany, June 2008, 2008, vol. 5096, p. 112--121.
B. H. Menze, Kelm, B. Michael, Masuch, R., Himmelreich, U., Bachert, P., Petrich, W., and Hamprecht, F. A., A Comparison of Random Forest and its Gini Importance with Standard Chemometric Methods for the Feature Selection and Classification of Spectral Data, BMC Bioinformatics, vol. 10:213, 2009.PDF icon Technical Report (675 KB)
P. Snoeij, van Halsema, D., Oost, W. A., Calkoen, C. J., Vogelzang, J., and Jähne, B., Comparison of microwave backscatter measurements and small-scale surface wave measurements made from the Dutch ocean research tower 'Noordwijk', in Proceedings IGARSS '91, 1991, vol. 3, p. 1289--1292.
M. Marxen, Sullivan, P. E., Loewen, M. R., and Jähne, B., Comparison of Gaussian particle center estimators and the achievable measurement density for particle tracking velocimetry, Exp. Fluids, vol. 29, pp. 145-153, 2000.
V. Kolmogorov and Rother, C., Comparison of energy minimization algorithms for highly connected graphs, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2006, vol. 3952 LNCS, pp. 1–15.
V. Kolmogorov and Rother, C., Comparison of energy minimization algorithms for highly connected graphs, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2006, vol. 3952 LNCS, pp. 1–15.
C. Weber, Zechmann, C. M., Kelm, B. Michael, Zamecnik, R., Hendricks, D., Waldherr, R., Hamprecht, F. A., Delorme, S., Bachert, P., and Ikinger, U., Comparison of correctness of manuel and automatic evaluation of MR-spectrum with prostrate cancer, Der Urologe, vol. 46, p. 1252, 2007.
P. A. Lange, Jähne, B., Tschiersch, J., and Ilmberger, J., Comparison between an amplitude-measuring wire and a slope-measuring laser water wave gauge, Rev. Sci. Instrum., vol. 53, p. 651--655, 1982.
F. O. Kaster, Weber, M. - A., and Hamprecht, F. A., Comparative Validation of Graphical Models for Learning Tumor Segmentations from Noisy Manual Annotations, in LNCS, 2011, vol. LNCS 6533, pp. 74-85.PDF icon Technical Report (544.56 KB)
J. H. Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Kim, S., Kausler, B. X., Kröger, T., Lellmann, J., Komodakis, N., Savchynskyy, B., and Rother, C., A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems, International Journal of Computer Vision, pp. 1-30, 2015.PDF icon Technical Report (1.5 MB)
J. H. Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Kim, S., Kausler, B. X., Kröger, T., Lellmann, J., Komodakis, N., Savchynskyy, B., and Rother, C., A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems, CoRR, 2014.
J. H. Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Kim, S., Kausler, B. X., Kröger, T., Lellmann, J., Komodakis, N., Savchynskyy, B., and Rother, C., A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems, Int.~J.~Comp.~Vision, 2015.PDF icon Technical Report (5.12 MB)
J. H. Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Kim, S., Kausler, B. X., Kröger, T., Lellmann, J., Komodakis, N., Savchynskyy, B., and Rother, C., A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems, CoRR, vol. abs/1404.0533, 2014.PDF icon Technical Report (3.32 MB)
J. H. Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Kim, S., Kausler, B. X., Kröger, T., Lellmann, J., Komodakis, N., Savchynskyy, B., and Rother, C., A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems, International Journal of Computer Vision, vol. 115, pp. 155–184, 2015.
J. H. Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Kim, S., Kausler, B. X., Kröger, T., Lellmann, J., Komodakis, N., Savchynskyy, B., and Rother, C., A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems, International Journal of Computer Vision, vol. 115, pp. 155–184, 2015.
J. H. Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Kim, S., Kausler, B. X., Kröger, T., Lellmann, J., Komodakis, N., Savchynskyy, B., and Rother, C., A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems, International Journal of Computer Vision, vol. 115, pp. 155–184, 2015.
J. H. Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Kim, S., Kausler, B. X., Lellmann, J., Komodakis, N., and Rother, C., A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problem, in CVPR, 2013.PDF icon Technical Report (1.35 MB)

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