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2010
K. Börner, Hermle, J., Sommer, C., Brown, N. P., Knapp, B., Glass, B., Torralba, G., Reymann, J., Beil, N., Beneke, J., Pepperkok, R., Schneider, R., and Ludwig, T., “From experimental setup to bioinformatics: An RNAi screening platform to identify host factors involved in HIV-1 replication”, Biotechnology Journal, vol. 5, pp. 39-49, 2010.PDF icon Technical Report (556.09 KB)
V. Lempitsky, Rother, C., Roth, S., and Blake, A., “Fusion moves for markov random field optimization”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 32, pp. 1392–1405, 2010.
V. Lempitsky, Rother, C., Roth, S., and Blake, A., “Fusion moves for markov random field optimization”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 32, pp. 1392–1405, 2010.
Z. Lin, Erz, M., and Jähne, B., “Multi-frequency multi-sampling fluorescence lifetime imaging using a high-speed line-scan camera”, in Optics, Photonics, and Digital Technologies for Multimedia Applications, 12--15 April 2010, Brussels, 2010, vol. 7723, p. 77231S.
M. Jehle and Jähne, B., “Optimal Lighting for Defect Detection: Illumination Systems, Machine Learning, and Practical Verification”, in Forum Bildverarbeitung, Regensburg, 02.-03.12.2010, 2010, pp. 301-312.
M. Jehle and Jähne, B., “Optimal lighting for defect detection: illumination systems, machine learning, and practical verification”, in Forum Bildverarbeitung, 2010, p. 241--252.
J. Lellmann, Lenzen, F., and Schnörr, C., “Optimality Bounds for Variational Relaxations of Optimal Partition Problems”, 2010.
J. Lellmann, Lenzen, F., and Schnörr, C., “Optimality Bounds for Variational Relaxations of Optimal Partition Problems”, 2010.
M. Erz and Jähne, B., “Optimierte Kameraauswahl für maschinelles Sehen durch standardisierte Charakterisierung des bildgebenden Systeme”, in Forum Bildverarbeitung, 2010, p. 155--166.
2009
F. Lauer, Bloch, G., and Vidal, R., “A Continuous Optimization Framework for Hybrid System Identification”, in submitted to Automatica, 2009.
J. Lellmann, Kappes, J. H., Yuan, J., Becker, F., Schnörr, C., Mórken, K., and Lysaker, M., “Convex Multi-Class Image Labeling by Simplex-Constrained Total Variation”, in Scale Space and Variational Methods in Computer Vision (SSVM 2009), 2009, vol. 5567, pp. 150-162.
J. Lellmann, Kappes, J. H., Yuan, J., Becker, F., Schnörr, C., Mórken, K., and Lysaker, M., “Convex Multi-Class Image Labeling by Simplex-Constrained Total Variation”, in Scale Space and Variational Methods in Computer Vision (SSVM 2009), 2009, vol. 5567, pp. 150-162.
J. Lellmann, Kappes, J. H., Yuan, J., Becker, F., Schnörr, C., Mórken, K., and Lysaker, M., “Convex Multi-Class Image Labeling by Simplex-Constrained Total Variation”, in Scale Space and Variational Methods in Computer Vision (SSVM 2009), 2009, vol. 5567, pp. 150-162.
J. Lellmann, Kappes, J. H., Yuan, J., Becker, F., and Schnörr, C., “Convex Multi-Class Image Labeling by Simplex-Constrained Total Variation”, in Scale Space and Variational Methods in Computer Vision (SSVM 2009), 2009, vol. 5567, pp. 150-162.PDF icon Technical Report (1.75 MB)
J. Lellmann, Kappes, J. H., Yuan, J., Becker, F., and Schnörr, C., “Convex Multi-Class Image Labeling by Simplex-Constrained Total Variation”, in Scale Space and Variational Methods in Computer Vision (SSVM 2009), 2009, vol. 5567, pp. 150-162.PDF icon Technical Report (1.75 MB)
J. Lellmann, Kappes, J. H., Yuan, J., Becker, F., and Schnörr, C., “Convex Multi-Class Image Labeling by Simplex-Constrained Total Variation”, in Scale Space and Variational Methods in Computer Vision (SSVM 2009), 2009, vol. 5567, pp. 150-162.PDF icon Technical Report (1.75 MB)
J. Lellmann, Becker, F., and Schnörr, C., “Convex Optimization for Multi-Class Image Labeling with a Novel Family of Total Variation Based Regularizers”, in Proceedings of the IEEE Conference on Computer Vision (ICCV 09) Kyoto, Japan, 2009, pp. 646-653.
J. Lellmann, Becker, F., and Schnörr, C., “Convex Optimization for Multi-Class Image Labeling with a Novel Family of Total Variation Based Regularizers”, in IEEE International Conference on Computer Vision (ICCV), 2009, p. 646 -- 653.PDF icon Technical Report (930.18 KB)
C. Thieke, Nix, O., Koehn, A., Floca, R., van Straaten, D., Hahn, H., Strauss, L. G., Siems, U., Graf, M., Pruem, H., Klein, J., Laue, H., and Kaster, F. O., “A framework and multi-application prototype for integrated radiological diagnostics and radiation therapy”, Strahlentherapie und Onkologie, vol. 185, p. 81, 2009.
V. Lempitsky, Kohli, P., Rother, C., and Sharp, T., “Image segmentation with a bounding box prior”, in Proceedings of the IEEE International Conference on Computer Vision, 2009, pp. 277–284.
F. Lauer and Schnörr, C., “Spectral Clustering of Linear Subspaces for Motion Segmentation”, in Proceedings of the IEEE Conference on Computer Vision (ICCV 09) Kyoto, Japan, in press, 2009, pp. 678-685.
F. Lauer and Schnörr, C., “Spectral Clustering of Linear Subspaces for Motion Segmentation”, in Proc.~IEEE Int.~Conf.~Computer Vision (ICCV'09), 2009.PDF icon Technical Report (1.12 MB)
F. Lauer and Schnörr, C., “Spectral Clustering of Linear Subspaces for Motion Segmentation”, in Proc. IEEE Int. Conf. Computer Vision (ICCV'09), Kyoto, Japan, 2009.
J. Yuan, Schnörr, C., and Steidl, G., “Total-Variation Based Piecewise Affine Regularization”, in Scale Space and Variational Methods in Computer Vision (SSVM 2009), 2009, vol. 5567, pp. 552-564.PDF icon Technical Report (478.04 KB)
J. Yuan, Schnörr, C., and Steidl, G., “Total-Variation Based Piecewise Affine Regularization”, in Scale Space and Variational Methods in Computer Vision (SSVM 2009), 2009, vol. 5567, pp. 552-564.PDF icon Technical Report (478.04 KB)
J. Yuan, Schnörr, C., and Steidl, G., “Total-Variation Based Piecewise Affine Regularization”, in Scale Space and Variational Methods in Computer Vision (SSVM 2009), 2009, vol. 5567, pp. 552-564.
J. Yuan, Schnörr, C., and Steidl, G., “Total-Variation Based Piecewise Affine Regularization”, in Scale Space and Variational Methods in Computer Vision (SSVM 2009), 2009, vol. 5567, pp. 552-564.
2008
J. Lellmann, Kappes, J. H., Yuan, J., Becker, F., and Schnörr, C., “Convex Multi-Class Image Labeling by Simplex-Constrained Total Variation”, IWR, University of Heidelberg, 2008.PDF icon Technical Report (2.6 MB)
V. Lempitsky, Roth, S., and Rother, C., “FusionFlow: Discrete-continuous optimization for optical flow estimation”, in 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 2008.
V. Lempitsky, Blake, A., and Rother, C., “Image segmentation by branch-and-mincut”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2008, vol. 5305 LNCS, pp. 15–29.
V. Lempitsky, Blake, A., and Rother, C., “Image segmentation by branch-and-mincut”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2008, vol. 5305 LNCS, pp. 15–29.
2007
B. H. Menze, Kelm, B. Michael, and Hamprecht, F. A., “From eigenspots to fisherspots -- latent spaces in the nonlinear detection of spot patterns in a highly variable background”, in Advances in data analysis, 2007, vol. 33, pp. 255-262.PDF icon Technical Report (248.87 KB)
V. Lempitsky, Rother, C., and Blake, A., “LogCut - Efficient graph cut optimization for markov random fields”, in Proceedings of the IEEE International Conference on Computer Vision, 2007.
C. Rother, Kolmogorov, V., Lempitsky, V., and Szummer, M., “Optimizing binary MRFs via extended roof duality”, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2007.
C. Rother, Kolmogorov, V., Lempitsky, V., and Szummer, M., “Optimizing Binary MRFs via Extended Roof Duality Technical Report MSR-TR-2007-46”, Computing, 2007.

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