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2012
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.
V. Lempitsky, Blake, A., and Rother, C., “Branch-and-mincut: Global optimization for image segmentation with high-level priors”, Journal of Mathematical Imaging and Vision, vol. 44, pp. 315–329, 2012.
M. Geese, Jähne, B., and Ruhnau, P., “CNN Based Dark Signal Non-Uniformity Estimation”, CNNA, pp. 1-6, 2012.
M. Geese, Ruhnau, P., and Jähne, B., “CNN based dark signal non-uniformity estimation”, in Cellular Nanoscale Networks and Their Applications (CNNA), 2012 13th International Workshop on, 2012, p. 1--6.
A. Shekhovtsov, Kohli, P., and Rother, C., “Curvature prior for MRF-based segmentation and shape inpainting”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, vol. 7476 LNCS, pp. 41–51.
A. Shekhovtsov, Kohli, P., and Rother, C., “Curvature prior for MRF-based segmentation and shape inpainting”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, vol. 7476 LNCS, pp. 41–51.
A. Shekhovtsov, Kohli, P., and Rother, C., “Curvature prior for MRF-based segmentation and shape inpainting”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, vol. 7476 LNCS, pp. 41–51.
M. Bleyer, Rhemann, C., and Rother, C., “Extracting 3D scene-consistent object proposals and depth from stereo images”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, vol. 7576 LNCS, pp. 467–481.
M. Bleyer, Rhemann, C., and Rother, C., “Extracting 3D scene-consistent object proposals and depth from stereo images”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, vol. 7576 LNCS, pp. 467–481.
M. Bleyer, Rhemann, C., and Rother, C., “Extracting 3D scene-consistent object proposals and depth from stereo images”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, vol. 7576 LNCS, pp. 467–481.
M. Bleyer, Rhemann, C., and Rother, C., “Extracting 3D scene-consistent object proposals and depth from stereo images”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, vol. 7576 LNCS, pp. 467–481.
B. Jähne, “Gas transfer at water surfaces”, Environmental Fluid Mechanics - Memorial Volume in honour of Professor Gerhard H. Jirka. CRC Press/Balkema, p. 389--404, 2012.
R. Rocholz, Fahle, P., and Jähne, B., “High speed and high resolution wave imaging to investigate the initial generation of wind waves at very small fetch”. 2012.
J. Jancsary, Nowozin, S., and Rother, C., “Loss-specific training of non-parametric image restoration models: A new state of the art”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, vol. 7578 LNCS, pp. 112–125.
J. Jancsary, Nowozin, S., and Rother, C., “Loss-specific training of non-parametric image restoration models: A new state of the art”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, vol. 7578 LNCS, pp. 112–125.
J. Jancsary, Nowozin, S., and Rother, C., “Non-parametric crfs for image labeling”, in NIPS Workshop Modern Nonparametric Methods in Machine Learning, 2012, pp. 1–5.
B. Y. Renard, Xu, B., Kirchner, M., Zickmann, F., Winter, D., Korten, S., Brattig, N., Tzur, A., Hamprecht, F. A., and Steen, H., “Overcoming species boundaries in peptide identification with BICEPS”, Molecular and Cellular Proteomics, vol. 11, 2012.PDF icon Technical Report (444.6 KB)
C. Kräuter, Richter, K. E., Mesarchaki, E., Rocholz, R., Williams, J., and Jähne, B., “Partitioning of the Trasfer Resistance between Air and Water”, in SOLAS Open Science Conference, Washington State, USA, 2012.
C. Kräuter, Richter, K. E., Mesarchaki, E., Rocholz, R., Williams, J., and Jähne, B., “Partitioning of the Trasfer Resistance between Air and Water”, in SOLAS Open Science Conference, Washington State, USA, 2012.
D. Kondermann, Abraham, S., Förstner, W., Gehrig, S., Imiya, A., Jähne, B., Klose, F., Magor, M., Mayer, H., Mester, R., Pajdla, T., Reulke, R., and Zimmer, H., “On Performance Analysis of Optical Flow Algorithms”, in Outdoor and Large-Scale Real-Worls Scene Analysis, Dagstuhl-Workshop 2011, 2012, vol. LNCS, pp. 329-355.
J. Jancsary, Nowozin, S., Sharp, T., and Rother, C., “Regression Tree Fields An efficient, non-parametric approach to image labeling problems”, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2012, pp. 2376–2383.
J. Jancsary, Nowozin, S., Sharp, T., and Rother, C., “Regression Tree Fields An efficient, non-parametric approach to image labeling problems”, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2012, pp. 2376–2383.
M. Geese, Ruhnau, P., and Jähne, B., “Scene based maximum likelihood PRNU and DSNU non uniformity correction”, in Forum Bildverarbeitung, 2012, p. 71--82.
K. E. Richter, Rocholz, R., and Jähne, B., “The Schmidt Number Dependency of Air-Sea Gas Exchange with Varying Surfactant Coverage”, in SOLAS Open Science Conference, Washington State, USA, 2012.
K. E. Richter, Rocholz, R., and Jähne, B., “The Schmidt Number Dependency of Air-Sea Gas Exchange with Varying Surfactant Coverage”, in SOLAS Open Science Conference, Washington State, USA, 2012.
P. Kohli, Nickisch, H., Rother, C., and Rhemann, C., “User-centric learning and evaluation of interactive segmentation systems”, International Journal of Computer Vision, vol. 100, pp. 261–274, 2012.
P. Kohli, Nickisch, H., Rother, C., and Rhemann, C., “User-centric learning and evaluation of interactive segmentation systems”, International Journal of Computer Vision, vol. 100, pp. 261–274, 2012.
A. Mansfield, Gehler, P., Van Gool, L., and Rother, C., “Visibility maps for improving seam carving”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, vol. 6554 LNCS, pp. 131–144.
D. Kiefhaber, Schaper, J., Rocholz, R., Zappa, C. J., Asher, W. E., Jessup, A. T., and Jähne, B., “Water Surface Topography Measurements with the Reflective Stereo Slope Gauge”, in AGU Ocean Science Meeting 2012, Salt Lake City, 2012.
S. Meister, Izadi, S., Kohli, P., Hämmerle, M., Rother, C., and Kondermann, D., “When Can We Use KinectFusion for Ground Truth Acquisition?”, in Workshop on Color-Depth Camera Fusion in Robotics, IEEE International Conference on Intelligent Robots and Systems, 2012.
2013
J. Röder, “Active Learning: New Approaches, and Industrial Applications”. 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)
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)
J. H. Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Sungwoong, K., Kausler, B. X., Lellmann, J., Komodakis, N., and Rother, C., “A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problems”, in CVPR 2013. Proceedings, 2013.PDF icon Technical Report (1.35 MB)

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