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Uhlmann, V, Haubold, C, Hamprecht, F A and Unser, M (2017). Diverse Shortest Paths for Bioimage Analysis. Bioinformatics. 1-3
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Funke, J, Andres, B, Hamprecht, F A, Cardona, A and Cook, M (2012). Efficient Automatic 3D-Reconstruction of Branching Neurons from EM Data. CVPR 2012. Proceedings. 1004-1011PDF icon Technical Report (1.64 MB)
Hader, S and Hamprecht, F A (2003). Efficient Density Clustering. Between Data Science and Applied Data Analysis. Springer. 39-48
Beier, T, Andres, B, Köthe, U and Hamprecht, F A (2016). An Efficient Fusion Move Algorithm for the Minimum Cost Lifted Multicut Problem. ECCV. Proceedings. Springer. LNCS 9906 715-730PDF icon Technical Report (4.89 MB)
Lichy, M P, Bachert, P, Hamprecht, F A, Weber, M - A, Debus, J, Schulz-Ertner, D, Kauczor, H - U and Schlemmer, H - P (2006). 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. 178 627-633
Andres, B, Kappes, J H, Köthe, U, Schnörr, C and Hamprecht, F A (2010). An Empirical Comparison of Inference Algorithms for Graphical Models with Higher Order Factors Using OpenGM. Pattern Recognition, Proc.~32th DAGM SymposiumPDF icon Technical Report (218.43 KB)
Andres, B, Kappes, J H, Köthe, U, Schnörr, C and Hamprecht, F A (2010). An Empirical Comparison of Inference Algorithms for Graphical Models with Higher Order Factors Using OpenGM. Pattern Recognition, Proc.~32th DAGM Symposium. 353-362
Kandemir, M, Zhang, C and Hamprecht, F A (2014). Empowering multiple instance histopathology cancer diagnosis by cell graphs. MICCAI. Proceedings. Springer. 8674 228-235PDF icon Technical Report (1.76 MB)
Cerrone, L, Zeilmann, A and Hamprecht, F A (2019). End-to-End Learned Random Walker for Seeded Image Segmentation. CVPR. Proceedings. 12559-12568
Hehn, T M, Kooij, J F P and Hamprecht, F A (2020). End-to-End Learning of Decision Trees and Forests. International Journal of Computer Vision. 128 997-1011
Hehn, T and Hamprecht, F A (2018). End-to-end Learning of Deterministic Decision Trees. German Conference on Pattern Recognition. Proceedings. Springer. LNCS 11269 612-627PDF icon Technical Report (1.4 MB)
Andres, B, Kondermann, C, Kondermann, D, Hamprecht, F A and Garbe, C S (2008). On errors-in-variables regression with arbitrary covariance and its application to optical flow estimation. IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2008. IEEE. 1--6
Andres, B, Kondermann, C, Kondermann, D, Köthe, U, Hamprecht, F A and Garbe, C S (2008). 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. 1-6PDF icon Technical Report (1.58 MB)
Draxler, F, Veschgini, K, Salmhofer, M and Hamprecht, F A (2018). Essentially No Barriers in Neural Network Energy Landscape. ICML. Proceedings. 80 1308--1317PDF icon Technical Report (685.93 KB)
Kelm, B Michael, Menze, B H, Nix, O, Zechmann, C M and Hamprecht, F A (2009). Estimating Kinetic Parameter Maps from Dynamic Contrast-Enhanced MRI using Spatial Prior Knowledge. IEEE Transaction on Medical Imaging. 28:10 1534-1547PDF icon Technical Report (419.8 KB)
Renard, B Y, Timm, W, Kirchner, M, Steen, J A J, Hamprecht, F A and Steen, H (2010). Estimating the Confidence of Peptide Identifications without Decoy Databases. Analytical Chemistry. 4314-4318PDF icon Technical Report (619.11 KB)
Kandemir, M, Rubio, J C, Schmidt, U, Wojek, C, Welbl, J, Ommer, B and Hamprecht, F A (2014). Event Detection by Feature Unpredictability in Phase-Contrast Videos of Cell Cultures. Medical Image Computing and Computer-Assisted Intervention. Springer. 154--161PDF icon Technical Report (2 MB)
Kandemir, M, Rubio, J C, Schmidt, U, Welbl, J, Ommer, B and Hamprecht, F A (2014). Event Detection by Feature Unpredictability in Phase-Contrast Videos of Cell Cultures. MICCAI. Proceedings. Springer. 154-161PDF icon Paper (2 MB)
Hamprecht, F A and Agrell, E (2003). Exploring a space of materials: spatial sampling design and subset selection. Experimental Design for Combinatorial and High Throughput Materials Development. WileyPDF icon Technical Report (2.28 MB)
F
Hamprecht, F A, Achleitner, U, Krismer, A C, Lindner, K H, Wenzel, V, Strohmenger, H - U, Thiel, W and van Gunsteren, W F (2001). Fibrillation power: An alternative method of ECG spectral analysis for prediction of countershock success in a porcine model of ventricular fibrillation. Resuscitation. 50 287-296
Garbe, C S, Schnörr, C and Jähne, B (2007). Fluid flow estimation through integration of physical flow configurations. Proceedings of the 29th DAGM Symposium on Pattern Recognition. Springer. 92--101
Wanner, S, Sommer, C, Rocholz, R, Jung, M, Hamprecht, F A and Jähne, B (2011). A framework for interactive visualization and classification of dynamical processes at the water surface. 16th International Workshop on Vision, Modelling and Visualization. Eurographics Association, Germany. 199--206
Wanner, S, Sommer, C, Rocholz, R, Hamprecht, F A and Jähne, B (2011). A Framework for Interactive Visualization and Classification of Dynamical Processes at the Water Surface. 16th International Workshop on Vision, Modelling and Visualization. Eurographics Association, Germany. 199-206PDF icon Technical Report (4.67 MB)
Menze, B H, Kelm, B Michael and Hamprecht, F A (2007). From eigenspots to fisherspots -- latent spaces in the nonlinear detection of spot patterns in a highly variable background. Advances in data analysis. Springer. 33 255-262PDF icon Technical Report (248.87 KB)
Jähne, B, Brocke, M, Eisele, H, Hader, S, Hamprecht, F A, Happold, W, Raisch, F and Restle, J (2002). Für Anspruchsvolle - Multidimensionale Bildverarbeitung in der Produktion. Qualität und Zuverlässigkeit. 47 1154-1159
Beier, T, Hamprecht, F A and Kappes, J H (2015). Fusion Moves for Correlation Clustering. CVPR. Proceedings. 3507-3516PDF icon Technical Report (1.19 MB)
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Röder, J, Tolosana-Delgado, R and Hamprecht, F A (2011). Gaussian process classification: singly versus doubly stochastic models, and new computational schemes. Stochastic Environmental Research & Risk Assessment. 25 (7) 865-879PDF icon Technical Report (672.68 KB)
von Borstel, M, Kandemir, M, Schmidt, P, Rao, M, Rajamani, K and Hamprecht, F A (2016). Gaussian process density counting from weak supervision. ECCV. Proceedings. Springer. LNCS 9905 365-380 PDF icon Technical Report (1.71 MB)
Haubold, C, Ales, J, Wolf, S and Hamprecht, F A (2016). A Generalized Successive Shortest Paths Solver for Tracking Dividing Targets. ECCV. Proceedings. Springer. LNCS 9911 566-582PDF icon Technical Report (1.18 MB)
Schmähling, J and Hamprecht, F A (2007). Generalizing the Abbott-Firestone curve by two new surface descriptors. Wear. 262 1360-1371PDF icon Technical Report (877.34 KB)
Hamprecht, F A, Scott, W R P and van Gunsteren, W F (1997). Generation of pseudo-native protein structures for threading. Proteins. 28 522-529
Köthe, U, Andres, B, Kröger, T and Hamprecht, F A (2010). Geometric Analysis of 3D Electron Microscopy Data. Proceedings of Workshop on Discrete Geometry and Mathematical Morphology (WADGMM). 22-26PDF icon Technical Report (1.43 MB)
Andres, B, Kröger, T, Briggmann, K L, Denk, W, Norogod, N, Knott, G W, Köthe, U and Hamprecht, F A (2012). Globally Optimal Closed-Surface Segmentation for Connectomics. ECCV 2012. Proceedings, Part 3. 778-791PDF icon Technical Report (2.72 MB)
Schiegg, M, Hanslovsky, P, Haubold, C, Köthe, U, Hufnagel, L and Hamprecht, F A (2015). Graphical Model for Joint Segmentation and Tracking of Multiple Dividing Cell. Bioinformatics. 31 948-956. http://bioinformatics.oxfordjournals.org/content/early/2014/11/17/bioinformatics.btu764.full.pdf?keytype=ref&ijkey=mTXWsiFrci7R8tcPDF icon Technical Report (534.29 KB)
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Lindner, R, Lou, X, Reinstein, J, Shoeman, R L, Hamprecht, F A and Winkler, A (2014). Hexicon 2: Automated Processing of Hydrogen-Deuterium Exchange Mass Spectrometry Data with Improved Deuteration Distribution Estimation. Journal of The American Society for Mass Spectrometry. 25 1018-1028PDF icon Technical Report (2.1 MB)

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