Publications

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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)
S. Hader and Hamprecht, F. A., Efficient Density Clustering, Between Data Science and Applied Data Analysis. Springer, pp. 39-48, 2003.
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)
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.
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. 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.
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)
L. Cerrone, Zeilmann, A., and Hamprecht, F. A., End-to-End Learned Random Walker for Seeded Image Segmentation, CVPR. Proceedings. pp. 12559-12568, 2019.
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.
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)
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)
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)
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)
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)
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)
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)
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F. A. Hamprecht, Achleitner, U., Krismer, A. C., Lindner, K. H., Wenzel, V., Strohmenger, H. - U., Thiel, W., and van Gunsteren, W. F., Fibrillation power: An alternative method of ECG spectral analysis for prediction of countershock success in a porcine model of ventricular fibrillation, Resuscitation, vol. 50, pp. 287-296, 2001.
C. S. Garbe, Schnörr, C., and Jähne, B., Fluid flow estimation through integration of physical flow configurations, in Proceedings of the 29th DAGM Symposium on Pattern Recognition, 2007, p. 92--101.
S. Wanner, Sommer, C., Rocholz, R., Jung, M., Hamprecht, F. A., and Jähne, B., A framework for interactive visualization and classification of dynamical processes at the water surface, in 16th International Workshop on Vision, Modelling and Visualization, 2011, p. 199--206.
S. Wanner, Sommer, C., Rocholz, R., Hamprecht, F. A., and Jähne, B., A Framework for Interactive Visualization and Classification of Dynamical Processes at the Water Surface, in 16th International Workshop on Vision, Modelling and Visualization, 2011, pp. 199-206.PDF icon Technical Report (4.67 MB)
B. H. Menze, Kelm, B. Michael, and Hamprecht, F. A., From eigenspots to fisherspots -- latent spaces in the nonlinear detection of spot patterns in a highly variable background, in Advances in data analysis, 2007, vol. 33, pp. 255-262.PDF icon Technical Report (248.87 KB)
B. Jähne, Brocke, M., Eisele, H., Hader, S., Hamprecht, F. A., Happold, W., Raisch, F., and Restle, J., Für Anspruchsvolle - Multidimensionale Bildverarbeitung in der Produktion, Qualität und Zuverlässigkeit, vol. 47, pp. 1154-1159, 2002.
T. Beier, Hamprecht, F. A., and Kappes, J. H., Fusion Moves for Correlation Clustering, in CVPR. Proceedings, 2015, pp. 3507-3516.PDF icon Technical Report (1.19 MB)
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J. Röder, Tolosana-Delgado, R., and Hamprecht, F. A., Gaussian process classification: singly versus doubly stochastic models, and new computational schemes, Stochastic Environmental Research & Risk Assessment, vol. 25 (7), pp. 865-879, 2011.PDF icon Technical Report (672.68 KB)
M. von Borstel, Kandemir, M., Schmidt, P., Rao, M., Rajamani, K., and Hamprecht, F. A., Gaussian process density counting from weak supervision, ECCV. Proceedings, vol. LNCS 9905. Springer, pp. 365-380 , 2016.PDF icon Technical Report (1.71 MB)
C. Haubold, Ales, J., Wolf, S., and Hamprecht, F. A., A Generalized Successive Shortest Paths Solver for Tracking Dividing Targets, ECCV. Proceedings, vol. LNCS 9911. Springer, pp. 566-582, 2016.PDF icon Technical Report (1.18 MB)
J. Schmähling and Hamprecht, F. A., Generalizing the Abbott-Firestone curve by two new surface descriptors, Wear, vol. 262, pp. 1360-1371, 2007.PDF icon Technical Report (877.34 KB)
F. A. Hamprecht, Scott, W. R. P., and van Gunsteren, W. F., Generation of pseudo-native protein structures for threading, Proteins, vol. 28, pp. 522-529, 1997.
U. Köthe, Andres, B., Kröger, T., and Hamprecht, F. A., Geometric Analysis of 3D Electron Microscopy Data, in Proceedings of Workshop on Discrete Geometry and Mathematical Morphology (WADGMM), 2010, pp. 22-26.PDF icon Technical Report (1.43 MB)
B. Andres, Kröger, T., Briggmann, K. L., Denk, W., Norogod, N., Knott, G. W., Köthe, U., and Hamprecht, F. A., Globally Optimal Closed-Surface Segmentation for Connectomics, in ECCV 2012. Proceedings, Part 3, 2012, pp. 778-791.PDF icon Technical Report (2.72 MB)
M. Schiegg, Hanslovsky, P., Haubold, C., Köthe, U., Hufnagel, L., and Hamprecht, F. A., Graphical Model for Joint Segmentation and Tracking of Multiple Dividing Cell, Bioinformatics, vol. 31, no. 6, pp. 948-956, 2015.PDF icon Technical Report (534.29 KB)

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