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2011
C. Rother and Kolmogorov, V., Interactive foreground extraction using graph cut, Advances in Markov \ldots, pp. 1–20, 2011.
K. E. Richter and Jähne, B., A laboratory study of the Schmidt number dependency of air-water gas transfer, in Gas Transfer at Water Surfaces 2010, 2011, p. 322--332.
K. E. Richter and Jähne, B., A laboratory study of the Schmidt number dependency of air-water gas transfer, in Gas Transfer at Water Surfaces 2010, 2011, p. 322--332.
D. Kiefhaber, Rocholz, R., Schaper, J., Balschbach, G., and Jähne, B., Mean square slope measurements in the field with the reflective stereo slope gauge, in EGU General Assembly, Vienna, 2011.
D. Kiefhaber, Rocholz, R., Balschbach, G., Schaper, J., and Jähne, B., Measurement of ocean wave statistics with the reflective stereo slope gauge, in DPG Frühjahrstagung Dresden, Fachverband Umweltphysik, 2011.
S. Vicente, Rother, C., and Kolmogorov, V., Object cosegmentation, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2011, pp. 2217–2224.
M. Bleyer, Rother, C., Kohli, P., Scharstein, D., and Sinha, S., Object stereo Joint stereo matching and object segmentation, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2011, pp. 3081–3088.
F. O. Kaster, Merkel, B., Nix, O., and Hamprecht, F. A., An object-oriented library for systematic training and comparison of classifiers for computer-assisted tumor diagnosis from MRSI measurements, Computer Science - Research and Development, vol. 26, pp. 65-85, 2011.PDF icon Technical Report (808.16 KB)
B. H. Menze, Kelm, B. Michael, Splitthoff, N., Köthe, U., and Hamprecht, F. A., On oblique random forests, in European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2011. Proceedings., 2011, pp. 453-469.PDF icon Technical Report (665.33 KB)
B. H. Menze, Kelm, B. Michael, Splitthoff, N., Köthe, U., and Hamprecht, F. A., On oblique random forests, in European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2011. Proceedings., 2011, pp. 453-469.PDF icon Technical Report (665.33 KB)
J. Lellmann, Lenzen, F., and Schnörr, C., Optimality Bounds for a Variational Relaxation of the Image Partitioning Problem, in Energy Min. Meth. Comp. Vis. Patt. Recogn., 2011, vol. 6819, pp. 132–146.
J. Lellmann, Lenzen, F., and Schnörr, C., Optimality Bounds for a Variational Relaxation of the Image Partitioning Problem, in Energy Min. Meth. Comp. Vis. Patt. Recogn., 2011, vol. 6819, p. 132--146.PDF icon Technical Report (1 MB)
A. Monroy, Kröger, T., Arnold, M., and Ommer, B., Parametric Object Detection for Iconographic Analysis, in Scientific Computing & Cultural Heritage, 2011.
B. Andres, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., Probabilistic Image Segmentation with Closedness Constraints, in ICCV, Proceedings, 2011, pp. 2611 - 2618.PDF icon Technical Report (8.18 MB)
B. Andres, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., Probabilistic Image Segmentation with Closedness Constraints, in Proceedings of ICCV, 2011.
B. Andres, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., Probabilistic Image Segmentation with Closedness Constraints, in ICCV, Proceedings, 2011, pp. 2611 - 2618.PDF icon Technical Report (8.18 MB)
B. Andres, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., Probabilistic Image Segmentation with Closedness Constraints, in Proceedings of ICCV, 2011.PDF icon Technical Report (2.95 MB)
B. Andres, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., Probabilistic Image Segmentation with Closedness Constraints, in Proceedings of ICCV, 2011.PDF icon Technical Report (2.95 MB)
B. Andres, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., Probabilistic Image Segmentation with Closedness Constraints, in Proceedings of ICCV, 2011.
P. Pletscher, Nowozin, S., Kohli, P., and Rother, C., Putting MAP back on the map, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2011, vol. 6835 LNCS, pp. 111–121.
P. Pletscher, Nowozin, S., Kohli, P., and Rother, C., Putting MAP back on the map, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2011, vol. 6835 LNCS, pp. 111–121.
P. Vincent Gehler, Rother, C., Kiefel, M., Zhang, L., and Schölkopf, B., Recovering intrinsic images with a global sparsity prior on reflectance, in Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011, NIPS 2011, 2011.
M. Hanselmann, Voss, B., Renard, B. Y., Lindner, M., Köthe, U., Kirchner, M., and Hamprecht, F. A., SIMA: Simultaneous Multiple Alignment of LC/MS Peak Lists, Bioinformatics, vol. 27 (7), pp. 987-993, 2011.PDF icon Technical Report (2.2 MB)
M. Hanselmann, Voss, B., Renard, B. Y., Lindner, M., Köthe, U., Kirchner, M., and Hamprecht, F. A., SIMA: Simultaneous Multiple Alignment of LC/MS Peak Lists, Bioinformatics, vol. 27 (7), pp. 987-993, 2011.PDF icon Technical Report (2.2 MB)
B. Savchynskyy, Kappes, J. H., Schmidt, S., and Schnörr, C., A Study of Nesterov's Scheme for Lagrangian Decomposition and MAP Labeling, in IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2011.PDF icon Technical Report (408.99 KB)
B. Savchynskyy, Kappes, J. H., Schmidt, S., and Schnörr, C., A Study of Nesterov's Scheme for Lagrangian Decomposition and MAP Labeling, IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), accepted as oral presentation, pp. 1817 - 1823, 2011.
B. Savchynskyy, Kappes, J. H., Schmidt, S., and Schnörr, C., A Study of Nesterov's Scheme for Lagrangian Decomposition and MAP Labeling, in IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2011.
L. Maier-Hein, Franz, A. M., Fangerau, M., Schmidt, M., Seitel, A., Mersmann, S., Kilgus, T., Groch, A., Yung, K., Santos, T. R. dos, and Meinzer, H. - P., Towards mobile augmented reality for on-patient visualization of medical images, in Bildverarbeitung für die Medizin (2011), 2011, p. 389--393.
B. Michael Kelm, Kaster, F. O., Henning, A., Weber, M. - A., Bachert, P., Bösinger, P., Hamprecht, F. A., and Menze, B. H., Using Spatial Prior Knowledge in the Spectral Fitting of Magnetic Resonance Spectroscopic Images, NMR in Biomedicine, vol. 25(1), pp. 1-13, 2011.PDF icon Technical Report (1.94 MB)
B. Michael Kelm, Kaster, F. O., Henning, A., Weber, M. - A., Bachert, P., Bösinger, P., Hamprecht, F. A., and Menze, B. H., Using Spatial Prior Knowledge in the Spectral Fitting of Magnetic Resonance Spectroscopic Images, NMR in Biomedicine, vol. 25(1), pp. 1-13, 2011.PDF icon Technical Report (1.94 MB)
F. Becker, Lenzen, F., Kappes, J. H., and Schnörr, C., Variational Recursive Joint Estimation of Dense Scene Structure and Camera Motion from Monocular High Speed Traffic Sequences, in 2011 IEEE International Conference on Computer Vision ICCV, 2011, pp. 1692-1699.
F. Becker, Lenzen, F., Kappes, J. H., and Schnörr, C., Variational Recursive Joint Estimation of Dense Scene Structure and Camera Motion from Monocular High Speed Traffic Sequences, in 2011 IEEE International Conference on Computer Vision (ICCV), 2011, p. 1692 -- 1699.PDF icon Technical Report (4.9 MB)
F. Becker, Lenzen, F., Kappes, J. H., and Schnörr, C., Variational Recursive Joint Estimation of Dense Scene Structure and Camera Motion from Monocular High Speed Traffic Sequences, in 2011 IEEE International Conference on Computer Vision (ICCV), 2011, pp. 1692 – 1699.
J. Kunz, Visualisierung der wasserseitigen Massengrenzschicht beim konvektionsgetriebenen Gasaustausch mithilfe einer Lumineszenzmethode und Thermografie, Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 2011.
M. Pfannmöller, Flügge, H., Benner, G., Wacker, I., Sommer, C., Hanselmann, M., Schmale, S., Schmidt, H., Hamprecht, F. A., Rabe, T., Kowalsky, W., and Schröder, R., Visualizing a homogeneous blend in bulk heterojunction polymer solar cells by analytical electron microscopy, Nano Letters, vol. 11, pp. 3099-3107, 2011.

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