Publications

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2014
D. Kainmueller, Jug, F., Rother, C., and Myers, G., Active graph matching for automatic joint segmentation and annotation of C. elegans, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2014, vol. 8673 LNCS, pp. 81–88.
X. Lou, Schiegg, M., and Hamprecht, F. A., Active Structured Learning for Cell Tracking: Algorithm, Framework and Usability, IEEE Transactions on Medical Imaging, vol. 33 (4), pp. 849-860, 2014.PDF icon Technical Report (6.84 MB)
L. Nagel, Active Thermography to Investigate Small-Scale Air-Water Transport Processes in the Laboratory and the Field, vol. Dissertation. Institut für Umweltphysik, Fakultät für Chemie und Geowissenschaften, Univ.\ Heidelberg, 2014.
K. Ellen Krall and Jähne, B., Air-sea gas exchange and momentum transfer: turbulence and Schmidt number dependency, in 7th SOPRAN Annual Meeting, Bremen, Germany, 25-26 March 2014, 2014.
K. Ellen Krall, Schneider-Zapf, K., Reith, S., Kiefhaber, D., and Jähne, B., Air-sea gas exchange under nature-like surfactant influence in the lab, in 7th SOPRAN Annual Meeting, Bremen, Germany, 25-26 March 2014, 2014.
M. Takami, Bell, P., and Ommer, B., An Approach to Large Scale Interactive Retrieval of Cultural Heritage, in Eurographics Workshop on Graphics and Cultural Heritage, 2014.PDF icon Technical Report (7.94 MB)
B. Güssefeld, Kondermann, D., Schwartz, C., and Klein, R., Are reflectance field renderings appropriate for optical flow evaluation?, in International Conference on Image Processing, ICIP 2014, 2014.
M. Horn, Arriving at Z / f, pp. 1–2, 2014.
T. Kröger, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., Asymmetric Cuts: Joint Image Labeling and Partitioning, in Pattern Recognition - 36th German Conference, {GCPR} 2014, Münster, Germany, September 2-5, 2014, Proceedings, 2014.PDF icon Technical Report (3.46 MB)
T. Kröger, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., Asymmetric Cuts: Joint Image Labeling and Partitioning, in 36th German Conference on Pattern Recognition, 2014.
A. - S. Wahl, Omlor, W., Rubio, J. C., Chen, J. L., Zheng, H., Schröter, A., Gullo, M., Weinmann, O., Kobayashi, K., Helmchen, F., Ommer, B., and Schwab, M. E., Asynchronous Therapy Restores Motor Control by Rewiring of the Rat Corticospinal Tract after Stroke, Science, vol. 344, p. 1250--1255, 2014.
C. Decker, Automated Animal Behavior Classification, University of Heidelberg, 2014.
B. F. Tek, Kröger, T., Mikula, S., and Hamprecht, F. A., Automated Cell Nucleus Detection for Large-Volume Electron Microscopy of Neural Tissue, in ISBI. Proceedings, 2014, pp. 69-72.PDF icon Technical Report (533.92 KB)
A. Kreshuk, Köthe, U., Pax, E., Bock, D. D., and Hamprecht, F. A., Automated Detection of Synapses in Serial Section Transmission Electron Microscopy Image Stacks, PLoS ONE, vol. 9, p. 2, 2014.PDF icon Technical Report (16.66 MB)
S. Petra and Schnörr, C., Average Case Recovery Analysis of Tomographic Compressive Sensing, Linear Algebra and its Applications, vol. 441, pp. 168-198, 2014.PDF icon Technical Report (1.85 MB)
2013
J. Röder, Active Learning: New Approaches, and Industrial Applications. University of Heidelberg, 2013.
F. Lenzen, Becker, F., and Lellmann, J., Adaptive Second-Order Total Variation: An Approach Aware of Slope Discontinuities, in Proceedings of the 4th International Conference on Scale Space and Variational Methods in Computer Vision SSVM, 2013, vol. 7893, pp. 61-73.
F. Lenzen, Becker, F., and Lellmann, J., Adaptive Second-Order Total Variation: An Approach Aware of Slope Discontinuities, in Proceedings of the 4th International Conference on Scale Space and Variational Methods in Computer Vision (SSVM) 2013, 2013, vol. 54, no. 2, p. 371--398.PDF icon Technical Report (702.08 KB)
P. Hanslovsky, Advanced Cell Tacking-by-Assignment, University of Heidelberg, 2013.
M. Sindeev, Konushin, A., and Rother, C., Alpha-flow for video matting, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2013, vol. 7726 LNCS, pp. 438–452.
F. Diego, Reichinnek, S., Both, M., and Hamprecht, F. A., Automated Identification of Neuronal Activity from Calcium Imaging by Sparse Dictionary Learning, ISBI 2013. Proceedings, pp. 1058-1061, 2013.PDF icon Technical Report (2.82 MB)
M. Arnold, Bell, P., and Ommer, B., Automated Learning of Self-Similarity and Informative Structures in Architecture, in Scientific Computing & Cultural Heritage, 2013.
R. Mikut, Dickmeis, T., Driever, W., Geurts, P., Hamprecht, F. A., Kausler, B. X., Ledesma-Carbayo, M., Marée, R., Mikula, K., Pantazis, P., Ronneberger, O., Santos, A., and Stotzka, R., Automated Processing of Zebrafish Imaging Data: A Survey, Zebrafish, vol. 10 (3), 2013.PDF icon Technical Report (1.73 MB)
2012
M. Hanselmann, Röder, J., Köthe, U., Renard, B. Y., Heeren, R. M. A., and Hamprecht, F. A., Active Learning for Convenient Annotation and Classification of Secondary Ion Mass Spectrometry Images, Analytical Chemistry, vol. 85 (1), pp. 147-155, 2012.PDF icon Technical Report (2.58 MB)
J. Röder, Kunzmann, K., Nadler, B., and Hamprecht, F. A., Active Learning with Distributional Estimates, UAI 2012. Proceedings, pp. 715-725, 2012.PDF icon Technical Report (267.67 KB)
L. Nagel, Richter, K. E., and Jähne, B., Active Thermography as a Link between Laboratory and Field Studies, in SOLAS Open Science Conference, Washington State, USA, 2012.
B. Jähne, Atmosphere-water exchange, Transport and Fate of Chemicals in the Environment --- selected Entries from the Encyclopedia of Sustainability Science and Technology, vol. 1. Springer, p. 175--193, 2012.
B. Jähne, Atmosphere-water exchange, Encyclopedia of Sustainable Science and Technology, vol. 1. Springer, p. 594--606, 2012.
A. Kreshuk, Automated Analysis of Biomedical Data from Low to High Resolution. University of Heidelberg, 2012.
C. M. Zechmann, Menze, B. H., Kelm, B. Michael, Zamecnik, P., Ikinger, U., Waldherr, R., Delorme, S., Hamprecht, F. A., and Bachert, P., Automated vs. manual pattern recognition of 3D 1H MRSI data of patients with prostate cancer, Academic Radiology, vol. 19, 6, pp. 675-684, 2012.

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