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Filters: Author is Fred A. Hamprecht and First Letter Of Title is E  [Clear All Filters]
2020
T. M. Hehn, Kooij, J. F. P., and Hamprecht, F. A., “End-to-End Learning of Decision Trees and Forests”, International Journal of Computer Vision, vol. 128, pp. 997-1011, 2020.
2019
L. Cerrone, Zeilmann, A., and Hamprecht, F. A., “End-to-End Learned Random Walker for Seeded Image Segmentation”, CVPR. Proceedings. pp. 12559-12568, 2019.
2018
T. Hehn and Hamprecht, F. A., “End-to-end Learning of Deterministic Decision Trees”, German Conference on Pattern Recognition. Proceedings, vol. LNCS 11269. Springer, pp. 612-627, 2018.PDF icon Technical Report (1.4 MB)
F. Draxler, Veschgini, K., Salmhofer, M., and Hamprecht, F. A., “Essentially No Barriers in Neural Network Energy Landscape”, ICML. Proceedings, vol. 80. p. 1308--1317, 2018.PDF icon Technical Report (685.93 KB)
2016
T. Beier, Andres, B., Köthe, U., and Hamprecht, F. A., “An Efficient Fusion Move Algorithm for the Minimum Cost Lifted Multicut Problem”, ECCV. Proceedings, vol. LNCS 9906. Springer, pp. 715-730, 2016.PDF icon Technical Report (4.89 MB)
2014
M. Kandemir, Zhang, C., and Hamprecht, F. A., “Empowering multiple instance histopathology cancer diagnosis by cell graphs”, in MICCAI. Proceedings, 2014, vol. 8674, pp. 228-235.PDF icon Technical Report (1.76 MB)
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)
2012
J. Funke, Andres, B., Hamprecht, F. A., Cardona, A., and Cook, M., “Efficient Automatic 3D-Reconstruction of Branching Neurons from EM Data”, CVPR 2012. Proceedings, pp. 1004-1011, 2012.PDF icon Technical Report (1.64 MB)
2010
B. Andres, Kappes, J. H., Köthe, U., Schnörr, C., and Hamprecht, F. A., “An Empirical Comparison of Inference Algorithms for Graphical Models with Higher Order Factors Using OpenGM”, in Pattern Recognition, Proc.~32th DAGM Symposium, 2010, pp. 353-362.
B. Andres, Kappes, J. H., Köthe, U., Schnörr, C., and Hamprecht, F. A., “An Empirical Comparison of Inference Algorithms for Graphical Models with Higher Order Factors Using OpenGM”, in Pattern Recognition, Proc.~32th DAGM Symposium, 2010.PDF icon Technical Report (218.43 KB)
B. Y. Renard, Timm, W., Kirchner, M., Steen, J. A. J., Hamprecht, F. A., and Steen, H., “Estimating the Confidence of Peptide Identifications without Decoy Databases”, Analytical Chemistry, pp. 4314-4318, 2010.PDF icon Technical Report (619.11 KB)
2009
B. Michael Kelm, Menze, B. H., Nix, O., Zechmann, C. M., and Hamprecht, F. A., “Estimating Kinetic Parameter Maps from Dynamic Contrast-Enhanced MRI using Spatial Prior Knowledge”, IEEE Transaction on Medical Imaging, vol. 28:10, pp. 1534-1547, 2009.PDF icon Technical Report (419.8 KB)
2008
B. Andres, Kondermann, C., Kondermann, D., Hamprecht, F. A., and Garbe, C. S., “On errors-in-variables regression with arbitrary covariance and its application to optical flow estimation”, in IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2008, 2008, p. 1--6.
B. Andres, Kondermann, C., Kondermann, D., Köthe, U., Hamprecht, F. A., and Garbe, C. S., “On errors-in-variables regression with arbitrary covariance and its application to optical flow estimation”, Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on, pp. 1-6, 2008.PDF icon Technical Report (1.58 MB)
2006
M. P. Lichy, Bachert, P., Hamprecht, F. A., Weber, M. - A., Debus, J., Schulz-Ertner, D., Kauczor, H. - U., and Schlemmer, H. - P., “Einsatz der 1H-MR-spektroskopischen Bildgebung in der Strahlentherapie: Cholin als Marker für die Bestimmung der relativen Wahrscheinlichkeit eines Tumorprogresses nach Bestrahlung glialer Hirntumoren”, Zeitung für Röntgenforschung, vol. 178, pp. 627-633, 2006.
2003
S. Hader and Hamprecht, F. A., “Efficient Density Clustering”, Between Data Science and Applied Data Analysis. Springer, pp. 39-48, 2003.
F. A. Hamprecht and Agrell, E., “Exploring a space of materials: spatial sampling design and subset selection”, Experimental Design for Combinatorial and High Throughput Materials Development. Wiley, 2003.PDF icon Technical Report (2.28 MB)