HCI Logo
Heidelberg University Logo
IWR Logo

Publications

Export 1229 results:
Author Title Type [ Year(Asc)]
Filters: First Letter Of Last Name is S  [Clear All Filters]
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.
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.
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)
L. Maier-Hein, Mersmann, S., Kondermann, D., Bodenstedt, S., Sanchez, A., Stock, C., Kenngott, H., Eisenmann, M., and Speidel, S., “Can masses of non-experts train highly accurate image classifiers? A crowdsourcing approach to instrument segmentation in laparoscopic images”, in MICCAI, 2014.
L. Maier-Hein, Mersmann, S., Kondermann, D., Bodenstedt, S., Sanchez, A., Stock, C., Kenngott, H., Eisenmann, M., and Speidel, S., “Can masses of non-experts train highly accurate image classifiers? A crowdsourcing approach to instrument segmentation in laparoscopic images”, in MICCAI, 2014.
L. Maier-Hein, Mersmann, S., Kondermann, D., Bodenstedt, S., Sanchez, A., Stock, C., Kenngott, H., Eisenmann, M., and Speidel, S., “Can masses of non-experts train highly accurate image classifiers? A crowdsourcing approach to instrument segmentation in laparoscopic images”, in MICCAI, 2014.
J. H. Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Kim, S., Kausler, B. X., Kröger, T., Lellmann, J., Komodakis, N., Savchynskyy, B., and Rother, C., “A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems”, CoRR, vol. abs/1404.0533, 2014.PDF icon Technical Report (3.32 MB)
J. H. Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Kim, S., Kausler, B. X., Kröger, T., Lellmann, J., Komodakis, N., Savchynskyy, B., and Rother, C., “A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems”, CoRR, vol. abs/1404.0533, 2014.PDF icon Technical Report (3.32 MB)
J. H. Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Kim, S., Kausler, B. X., Kröger, T., Lellmann, J., Komodakis, N., Savchynskyy, B., and Rother, C., “A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems”, CoRR, 2014.
J. H. Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Kim, S., Kausler, B. X., Kröger, T., Lellmann, J., Komodakis, N., Savchynskyy, B., and Rother, C., “A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems”, CoRR, 2014.
L. Maier-Hein, Mersmann, S., Kondermann, D., Stock, C., Kenngott, H., Sanchez, A., Wagner, M., Preukschas, A., Wekerle, A. - L., Helfert, S., Bodenstedt, S., and Speidel, S., “Crowdsourcing for reference correspondence generation in endoscopic images”, in MICCAI, 2014.
L. Maier-Hein, Mersmann, S., Kondermann, D., Stock, C., Kenngott, H., Sanchez, A., Wagner, M., Preukschas, A., Wekerle, A. - L., Helfert, S., Bodenstedt, S., and Speidel, S., “Crowdsourcing for reference correspondence generation in endoscopic images”, in MICCAI, 2014.
L. Maier-Hein, Mersmann, S., Kondermann, D., Stock, C., Kenngott, H., Sanchez, A., Wagner, M., Preukschas, A., Wekerle, A. - L., Helfert, S., Bodenstedt, S., and Speidel, S., “Crowdsourcing for reference correspondence generation in endoscopic images”, in MICCAI, 2014.
S. Zheng, Cheng, M. Ming, Warrell, J., Sturgess, P., Vineet, V., Rother, C., and Torr, P. H. S., “Dense semantic image segmentation with objects and attributes”, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2014, pp. 3214–3221.
E. Eyjolfsdottir, Branson, S., Burgos-Artizzu, X. P., Hoopfer, E. D., Schor, J., Anderson, D. J., and Perona, P., “Detection of social actions in fruit flies”, Lecture Notes in Computer Science, vol. 8690, pp. 772–787, 2014.
E. Eyjolfsdottir, Branson, S., Burgos-Artizzu, X. P., Hoopfer, E. D., Schor, J., Anderson, D. J., and Perona, P., “Detection of social actions in fruit flies”, Lecture Notes in Computer Science, vol. 8690, pp. 772–787, 2014.
A. Denitiu, Petra, S., Schnörr, C., and Schnörr, C., “An Entropic Perturbation Approach to TV-Minimization for Limited-Data Tomography”, in Discrete Geometry for Computer Imagery (DGCI) 2014, 2014, p. 262--274.PDF icon Technical Report (894.83 KB)
A. Denitiu, Petra, S., Schnörr, C., and Schnörr, C., “An Entropic Perturbation Approach to TV-Minimization for Limited-Data Tomography”, in Discrete Geometry for Computer Imagery (DGCI) 2014, 2014, p. 262--274.PDF icon Technical Report (894.83 KB)
A. Denitiu, Petra, S., Schnörr, C., and Schnörr, C., “An Entropic Perturbation Approach to TV-Minimization for Limited-Data Tomography”, in Discrete Geometry for Computer Imagery (DGCI) 2014, 2014, pp. 262–274.
A. Denitiu, Petra, S., Schnörr, C., and Schnörr, C., “An Entropic Perturbation Approach to TV-Minimization for Limited-Data Tomography”, in Discrete Geometry for Computer Imagery (DGCI) 2014, 2014, pp. 262–274.
M. Kandemir, Rubio, J. C., Schmidt, U., Wojek, C., Welbl, J., Ommer, B., and Hamprecht, F. A., “Event Detection by Feature Unpredictability in Phase-Contrast Videos of Cell Cultures”, in Medical Image Computing and Computer-Assisted Intervention, 2014, p. 154--161.PDF icon Technical Report (2 MB)
M. Kandemir, Rubio, J. C., Schmidt, U., Welbl, J., Ommer, B., and Hamprecht, F. A., “Event Detection by Feature Unpredictability in Phase-Contrast Videos of Cell Cultures”, in MICCAI. Proceedings, 2014, pp. 154-161.PDF icon Paper (2 MB)
M. Knorr, Esparza, J., Niehsen, W., and Stiller, C., “Extrinsic calibration of a fisheye multi-camera setup using overlapping fields of view”, in Intelligent Vehicles Symposium Proceedings, 2014, p. 1276--1281.
B. Schmitzer and Schnörr, C., “Globally Optimal Joint Image Segmentation and Shape Matching based on Wasserstein Modes”. 2014.
B. Schmitzer and Schnörr, C., “Globally Optimal Joint Image Segmentation and Shape Matching based on Wasserstein Modes”. 2014.
B. Schmitzer and Schnörr, C., “Globally Optimal Joint Image Segmentation and Shape Matching based on Wasserstein Modes”. 2014.PDF icon Technical Report (2.9 MB)
B. Schmitzer and Schnörr, C., “Globally Optimal Joint Image Segmentation and Shape Matching based on Wasserstein Modes”. 2014.PDF icon Technical Report (2.9 MB)
R. Lindner, Lou, X., Reinstein, J., Shoeman, R. L., Hamprecht, F. A., and Winkler, A., “Hexicon 2: Automated Processing of Hydrogen-Deuterium Exchange Mass Spectrometry Data with Improved Deuteration Distribution Estimation”, Journal of The American Society for Mass Spectrometry, vol. 25, pp. 1018-1028, 2014.PDF icon Technical Report (2.1 MB)
C. N. Straehle, “Interactive Segmentation, Uncertainty and Learning”. University of Heidelberg, 2014.
J. H. Kappes, Beier, T., and Schnörr, C., “MAP-Inference on Large Scale Higher-Order Discrete Graphical Models by Fusion Moves”, in Computer Vision - {ECCV} 2014 Workshops - Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part {II}, 2014.PDF icon Technical Report (557.49 KB)
J. Hendrik Kappes, Beier, T., and Schnörr, C., “MAP-Inference on Large Scale Higher-Order Discrete Graphical Models by Fusion Moves”, in International Workshop on Graphical Models in Computer Vision, 2014.
H. Schäfer, Lenzen, F., and Garbe, C. S., “Model based scattering correction in time-of-flight cameras”, Optics Express, vol. 22, pp. 29835-29846, 2014.
C. N. Straehle, Kandemir, M., Köthe, U., and Hamprecht, F. A., “Multiple instance learning with response-optimized random forests”, in ICPR. Proceedings, 2014, pp. 3768 - 3773.PDF icon Technical Report (296.66 KB)
F. Becker, Petra, S., and Schnörr, C., “Optical Flow”, Handbook of Mathematical Methods in Imaging. Springer, 2014.
F. Becker, Petra, S., and Schnörr, C., “Optical Flow”, Handbook of Mathematical Methods in Imaging. Springer, 2014.

Pages