Publications

Export 1965 results:
Author [ Title(Asc)] Type Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
C
Lellmann, J and Schnörr, C (2011). Continuous Multiclass Labeling Approaches and Algorithms. SIAM J.~Imag.~Sci. 4 1049-1096PDF icon Technical Report (4.31 MB)
Lellmann, J and Schnörr, C (2011). Continuous Multiclass Labeling Approaches and Algorithms. CoRR. abs/1102.5448. http://arxiv.org/abs/1102.5448
Lellmann, J and Schnörr, C (2010). Continuous Multiclass Labeling Approaches And Algorithms. Univ. of Heidelberg. http://www.ub.uni-heidelberg.de/archiv/10460/
Fundana, K, Heyden, A, Gosch, C and Schnörr, C (2008). Continuous Graph Cuts for Prior-Based Object Segmentation. 19th Int.~Conf.~Patt.~Recog.~(ICPR). 1--4PDF icon Technical Report (414.89 KB)
Jähne, B, Jähne, B, Haußecker, H and Geißler, P (1999). Continuous and digital signals. Handbook of Computer Vision and Applications. Academic Press. 2 9--34
Nair, R (2010). Construction And Analysis Of Random Tree Ensembles. University of Heidelberg
Schiegg, M, Hanslovsky, P, Kausler, B X, Hufnagel, L and Hamprecht, F A (2013). Conservation Tracking. ICCV 2013. Proceedings. 2928--2935PDF icon Technical Report (5.22 MB)
Kluger, F, Brachmann, E, Ackermann, H, Rother, C, Yang, M Ying and Rosenhahn, B (2020). CONSAC: Robust Multi-Model Fitting by Conditional Sample Consensus. CVPR 2020. http://arxiv.org/abs/2001.02643PDF icon PDF (9.95 MB)
Arnab, A, Zheng, S, Jayasumana, S, Romera-paredes, B, Kirillov, A, Savchynskyy, B, Rother, C, Kahl, F and Torr, P (2018). Conditional Random Fields Meet Deep Neural Networks for Semantic Segmentation. Cvpr. XX 1–15. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.308.8889&rep=rep1&type=pdf%0Ahttp://dx.doi.org/10.1109/CVPR.2012.6248050
Hanselmann, M, Kirchner, M, Renard, B Y, Amstalden, E R, Glunde, K, Heeren, R M A and Hamprecht, F A (2008). Concise Representation of MS Images by Probabilistic Latent Semantic Analysis. Analytical Chemistry. 80 9649-9658PDF icon Technical Report (3.91 MB)
Haußecker, H and Fleet, D J (2001). Computing optical flow with physical models of brightness variation. IEEE Trans. Pattern Analysis Machine Intelligence. 23 661--673
Kandemir, M and Hamprecht, F A (2014). Computer-aided diagnosis from weak supervision: A benchmarking study. Computerized Medical Imaging and Graphics. 42 44-50PDF icon Technical Report (4.28 MB)
Bell, P and Ommer, B (2018). Computer Vision und Kunstgeschichte — Dialog zweier Bildwissenschaften. Computing Art Reader: Einführung in die digitale Kunstgeschichte, P. Kuroczyński et al. (ed.)PDF icon 413-17-83318-2-10-20181210.pdf (2.98 MB)
Jähne, B and Haußecker, H (2000). Computer Vision And Applications: A Guide For Students And Practitioners. Academic Press
Wulf, M, Stiehl, H S and Schnörr, C (2000). On the computational rôle of the primate retina. Proc. 2nd ICSC Symposium on Neural Computation (NC 2000). Berlin, Germany
Kirchner, M, Renard, B Y, Köthe, U, Pappin, D J, Hamprecht, F A, Steen, J A J and Steen, H (2010). Computational Protein Profile Similarity Screening for Quantitative Mass Spectrometry Experiments. Bioinformatics. 26 (1) 77-83PDF icon Technical Report (380.19 KB)
Hanselmann, M (2010). Computational Methods for the Analysis of Mass Spectrometry Images. University of Heidelberg
Rathke, F and Schnörr, C (2015). A Computational Approach to Log-Concave Density Estimation. An. St. Univ. Ovidius Constanta. 23 151-166PDF icon Technical Report (1.07 MB)
Rathke, F and Schnörr, C (2015). A Computational Approach to Log-Concave Density Estimation. An. St. Univ. Ovidius Constanta. 23 151-166
Keränen, S V E, 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 (2009). Computational Analysis of Quantitative Changes in Gene Expression and Embryo Morphology between Species. Evolution-The Molecular Landscape
Schnörr, (1992). Computation of Discontinuous Optical Flow by Domain Decomposition and Shape Optimization. ijcv. 8 153–165
Schnörr, (1990). Computation of Discontinuous Optical Flow by Domain Decomposition and Shape Optimization. Proc. British Machine Vision Conference. Oxford/UK. 109–114
Dalitz, R, Petra, S and Schnörr, C (2017). Compressed Motion Sensing. Proc. SSVM. Springer. 10302
Hering, F, Haußecker, H, Dieter, J, Netzsch, T and Jähne, B (1997). A comprehensive study of algorithms for multidimensional flow field diagnostics. Proc. Optical 3D Measurement Techniques IV, Zurich, Sept. 29 - Oct. 2, 1997. Wichmann. 436--443
Ommer, B and Buhmann, J M (2003). A Compositionality Architecture for Perceptual Feature Grouping. Proceedings of the International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition. Springer. 2683 275--290PDF icon Technical Report (2.89 MB)
Ommer, B and Buhmann, J M (2007). Compositional Object Recognition, Segmentation, and Tracking in Video. Proceedings of the International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition. Springer. 4679 318--333PDF icon Technical Report (2.78 MB)
Jähne, (2007). Complex Motion, Proceedings Of The 1St Workshop, Günzburg, October 2004. Springer
Jähne, B and Jähne, B (2007). Complex motion in environmental physics and live sciences. Complex Motion. Springer. 3417 92--105
van Halsema, D, Calkoen, C J, Oost, W A, Snoeij, P and Jähne, B (1989). Comparisons of X-band Radar Backscatter Measurements with Area extended wave slop measurements made in a large Wind/Wave Tank. Proc. IGARSS'89. 5 2997--3001
van Halsema, D, Calkoen, C J, Oost, W A, Snoeij, P, Vogelzang, J and Jähne, B (1992). Comparisons of backscattering calculations with measurements made in a large wind/wave flume. Proc. IGARSS'92. 2 1451--1453
Haja, A, Abraham, S and Jähne, B (2008). A Comparison of Region Detectors for Tracking. Pattern Recognition, Proceedings 30th DAGM Symposium, Munich, Germany, June 2008. 5096 112--121
Menze, B H, Kelm, B Michael, Masuch, R, Himmelreich, U, Bachert, P, Petrich, W and Hamprecht, F A (2009). A Comparison of Random Forest and its Gini Importance with Standard Chemometric Methods for the Feature Selection and Classification of Spectral Data. BMC Bioinformatics. 10:213PDF icon Technical Report (675 KB)
Snoeij, P, van Halsema, D, Oost, W A, Calkoen, C J, Vogelzang, J and Jähne, B (1991). Comparison of microwave backscatter measurements and small-scale surface wave measurements made from the Dutch ocean research tower 'Noordwijk'. Proceedings IGARSS '91. 3 1289--1292
Marxen, M, Sullivan, P E, Loewen, M R and Jähne, B (2000). Comparison of Gaussian particle center estimators and the achievable measurement density for particle tracking velocimetry. Exp. Fluids. 29 145-153
Kolmogorov, V and Rother, C (2006). Comparison of energy minimization algorithms for highly connected graphs. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 3952 LNCS 1–15

Pages