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2008

D. Kondermann, Kondermann, C., Berthe, A., Kertzscher, U., and Garbe, C. S., “Motion Estimation Based on a Temporal Model of Fluid Flows”, in 13th International Symposium on Flow Visualization, 2008, pp. 1-10.

D. Kondermann, Kondermann, C., Berthe, A., Kertzscher, U., and Garbe, C. S., “Motion Estimation Based on a Temporal Model of Fluid Flows”, in 13th International Symposium on Flow Visualization, 2008, pp. 1-10.

D. Kondermann, Kondermann, C., Berthe, A., Kertzscher, U., and Garbe, C. S., “Motion Estimation Based on a Temporal Model of Fluid Flows”, in 13th International Symposium on Flow Visualization, 2008, pp. 1-10.

B. Y. Renard, Kirchner, M., Steen, H., Steen, J. A. J., and Hamprecht, F. A., “NITPICK: Peak Identification for Mass Spectrometry Data”, BMC Bioinformatics, vol. 9, p. 355, 2008.

Technical Report (643.89 KB)

C. S. Garbe, Krajsek, K., Pavlov, P., Andres, B., Mühlich, M., Stuke, I., Mota, C., Böhme, M., Haker, M., Schuchert, T., Scharr, H., Aach, T., and Barth, E., “Nonlinear Analysis of Multi-Dimensional Signals”, Mathematical Methods in Signal Processing and Digital Image Analysis. Springer, pp. 231-288, 2008.

Technical Report (7.11 MB)

C. S. Garbe, Krajsek, K., Pavlov, P., Andres, B., Mühlich, M., Stuke, I., Mota, C., Böhme, M., Haker, M., Schuchert, T., Scharr, H., Aach, T., and Barth, E., “Nonlinear Analysis of Multi-Dimensional Signals”, Mathematical Methods in Signal Processing and Digital Image Analysis. Springer, pp. 231-288, 2008.

Technical Report (7.11 MB)

C. S. Garbe, Krajsek, K., Pavlov, P., Andres, B., Mühlich, M., Stuke, I., Mota, C., Böhme, M., Haker, M., Schucher, T., Scharr, H., Aach, T., and Barth, E., “Nonlinear analysis of multi-dimensional signals: local adaptive estimation of complex motion and orientation patterns”, Mathematical Methods in Time Series Analysis and Digital Image Processing. Springer, pp. 231-288, 2008.

C. S. Garbe, Krajsek, K., Pavlov, P., Andres, B., Mühlich, M., Stuke, I., Mota, C., Böhme, M., Haker, M., Schucher, T., Scharr, H., Aach, T., and Barth, E., “Nonlinear analysis of multi-dimensional signals: local adaptive estimation of complex motion and orientation patterns”, Mathematical Methods in Time Series Analysis and Digital Image Processing. Springer, pp. 231-288, 2008.

J. Klappstein, “Optical-Flow based Detection of Moving Objects in Traffic Scenes”. IWR, Fakultät für Mathematik und Informatik, Univ.\ Heidelberg, 2008.

P. Kohli, Shekhovtsov, A., Rother, C., Kolmogorov, V., and Torr, P., “On partial optimality in multi-label MRFs”, in Proceedings of the 25th International Conference on Machine Learning, 2008, pp. 480–487.

P. Kohli, Shekhovtsov, A., Rother, C., Kolmogorov, V., and Torr, P., “On partial optimality in multi-label MRFs”, in Proceedings of the 25th International Conference on Machine Learning, 2008, pp. 480–487.

C. Kondermann, Kondermann, D., and Garbe, C. S., “Postprocessing of optical flows via surface measures and motion inpainting”, in Pattern Recognition, 2008, vol. 5096, p. 355--364.

C. Kondermann, Kondermann, D., and Garbe, C. S., “Postprocessing of optical flows via surface measures and motion inpainting”, in Pattern Recognition, 2008, vol. 5096, p. 355--364.

U. Köthe, “Reliable Low-Level Image Analysis”, Habilitation thesis. Department Informatik, University of Hamburg, Hamburg, 2008.

Technical Report (12.44 MB)

T. König, Menze, B. H., Kirchner, M., Monigatti, F., Parker, K. C., Patterson, T., Steen, J. J., Hamprecht, F. A., and Steen, H., “Robust Prediction of the MASCOT Score for an Improved Quality Assessment in Mass Spectrometric Proteomics”, Journal of Proteome Research, vol. 7, pp. 3708-3717, 2008.

Technical Report (1.16 MB)

T. König, Menze, B. H., Kirchner, M., Monigatti, F., Parker, K. C., Patterson, T., Steen, J. J., Hamprecht, F. A., and Steen, H., “Robust Prediction of the MASCOT Score for an Improved Quality Assessment in Mass Spectrometric Proteomics”, Journal of Proteome Research, vol. 7, pp. 3708-3717, 2008.

Technical Report (1.16 MB)

B. Andres, Köthe, U., Helmstaedter, M., Denk, W., and Hamprecht, F. A., “Segmentation of SBFSEM Volume Data of Neural Tissue by Hierarchical Classification”, in Pattern Recognition. 30th DAGM Symposium Munich, Germany, June 10-13, 2008. Proceedings, 2008, vol. 5096, pp. 142-152.

Technical Report (1.21 MB)

C. Kondermann, Mester, R., and Garbe, C. S., “A statistical confidence measure for optical flows”, in Proceedings of the ECCV, 2008, vol. 5304, p. 290--301.

H. Meine, Köthe, U., and Stelldinger, P., “A Topological Sampling Theorem for Robust Boundary Reconstruction and Image Segmentation”, Discrete Applied Mathematics, vol. 157, pp. 524-541, 2008.

M. Jäger, Knoll, C., and Hamprecht, F. A., “Weakly Supervised Learning of a Classifier for Unusual Event Detection”, IEEE Transactions on Image Processing, vol. 17, pp. 1700-1708, 2008.

Technical Report (295.32 KB)

U. Köthe, “What Can We Learn from Discrete Images about the Continuous World”, Discrete Geometry for Computer Imagery, vol. 4992. Springer, pp. 4-19, 2008.

2007

C. Kondermann, Kondermann, D., Jähne, B., Garbe, C. S., Schnörr, C., and Jähne, B., “An adaptive confidence measure for optical flows based on linear subspace projections”, in Proceedings of the 29th DAGM Symposium on Pattern Recognition, 2007, vol. 4713, p. 132--141.

C. Kondermann, Kondermann, D., Jähne, B., Garbe, C. S., Schnörr, C., and Jähne, B., “An adaptive confidence measure for optical flows based on linear subspace projections”, in Proceedings of the 29th DAGM Symposium on Pattern Recognition, 2007, vol. 4713, p. 132--141.

M. Kirchner, Saussen, B., Steen, H., Steen, J. A. J., and Hamprecht, F. A., “amsrpm: Robust Point Matching in Retention Time Alignment of LC/MS Data with R”, Journal of Statistical Software, vol. 18, pp. 1-12, 2007.

V. Kolmogorov, Boykov, Y., and Rother, C., “Applications of parametric maxflow in computer vision”, in Proceedings of the IEEE International Conference on Computer Vision, 2007.

V. Kolmogorov, Boykov, Y., and Rother, C., “Applications of parametric maxflow in computer vision”, in Proceedings of the IEEE International Conference on Computer Vision, 2007.

B. Michael Kelm, Menze, B. H., Zechmann, C. M., Baudendistel, K. T., and Hamprecht, F. A., “Automated Estimation of Tumor Probability in Prostate MRSI: Pattern Recognition vs. Quantification”, Magnetic Resonance in Medicine, vol. 57, pp. 150-159, 2007.

Technical Report (348.05 KB)

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.

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.

B. Jähne, Klar, M., and Jehle, M., “Data analysis”, Handbook of Experimental Fluid Mechanics. Springer, p. 1437--1491, 2007.

J. Scholz, Wiersbinski, T., Ruhnau, P., Kondermann, D., Garbe, C. S., Hain, R., and Beushausen, V., “Double-pulse planar-LIF investigations using fluorescence motion analysis for mixture formation investigation”, in 7th International Symposium on Particle Image Velocimetry Rome, 11. - 14.Sept., 2007.

B. Michael Kelm, “Evaluation of Vector-Valued Clinical Image Data Using Probabilistic Graphical Models: Quantification and Pattern Recognition”. University of Heidelberg, 2007.

Technical Report (4.89 MB)

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.

Technical Report (248.87 KB)

A. Blake, Criminisi, A., Cross, G., Kolmogorov, V., and Rother, C., “Fusion of stereo, colour and contrast”, Springer Tracts in Advanced Robotics, vol. 28, 2007.

Pages