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Kappes, J Hendrik, Speth, M, Reinelt, G and Schnörr, C (2013). Higher-order Segmentation via Multicuts. ArXiv e-prints

Kappes, J H, 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 (2015). A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems. Int.~J.~Comp.~Vision

Technical Report (5.12 MB)

Kappes, J H, Petra, S, Schnörr, C and Zisler, M (2015). TomoGC: Binary Tomography by Constrained Graph Cuts. Proc.~GCPR

Technical Report (2.46 MB)

Kappes, J H, Swoboda, P, Savchynskyy, B, Hazan, T and Schnörr, C (2015). Probabilistic Correlation Clustering and Image Partitioning Using Perturbed Multicuts. Proc.~SSVM. Springer

Technical Report (1.1 MB)

Kappes, J H, Schmidt, S and Schnörr, C (2010). MRF Inference by k-Fan Decomposition and Tight Lagrangian Relaxation. European Conference on Computer Vision (ECCV). Springer Berlin / Heidelberg. 6313 735--747

Technical Report (1.49 MB)

Kappes, J H and Schnörr, C (2008). MAP-Inference for Highly-Connected Graphs with DC-Programming. Pattern Recognition -- 30th DAGM Symposium. Springer Verlag. 5096 1--10

Technical Report (1.91 MB)

Kappes, J H, Speth, M, Andres, B, Reinelt, G and Schnörr, C (2011). Globally Optimal Image Partitioning by Multicuts. EMMCVPR. Springer

Technical Report (7.47 MB)

Kappes, J H, 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 (2014). A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems. CoRR. abs/1404.0533. http://hci.iwr.uni-heidelberg.de/opengm2/

Technical Report (3.32 MB)

Kappes, J H, Andres, B, Hamprecht, F A, Schnörr, C, Nowozin, S, Batra, D, Kim, S, Kausler, B X, Lellmann, J, Komodakis, N and Rother, C (2013). A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problem. CVPR

Technical Report (1.35 MB)

Kappes, J H, Savchynskyy, B and Schnörr, C (2012). A Bundle Approach To Efficient MAP-Inference by Lagrangian Relaxation. CVPR

Technical Report (430.63 KB)

Kappes, J H, Speth, M, Reinelt, G and Schnörr, C (2013). Towards Efficient and Exact MAP-Inference for Large Scale Discrete Computer Vision Problems via Combinatorial Optimization. CVPR

Technical Report (623.84 KB)

Kappes, J H, Speth, M, Reinelt, G and Schnörr, C (2013). Higher-order Segmentation via Multicuts. ArXiv e-prints

Technical Report (1.07 MB)

Kappes, J H, Beier, T and Schnörr, C (2014). MAP-Inference on Large Scale Higher-Order Discrete Graphical Models by Fusion Moves. Computer Vision - {ECCV} 2014 Workshops - Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part {II}. http://dx.doi.org/10.1007/978-3-319-16181-5_37

Technical Report (557.49 KB)

Kappes, J H, 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 (2015). A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems. International Journal of Computer Vision. 1-30

Technical Report (1.5 MB)

Kappes, J H, Andres, B, Hamprecht, F A, Schnörr, C, Nowozin, S, Batra, D, Sungwoong, K, Kausler, B X, Lellmann, J, Komodakis, N and Rother, C (2013). A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problems. CVPR 2013. Proceedings

Technical Report (1.35 MB)

Kappes, J H, Speth, M, Andres, B, Reinelt, G and Schnörr, C (2011). Globally Optimal Image Partitioning by Multicuts. EMMCVPR. Springer. 31-44

Technical Report (7.3 MB)

Kappes, J H, 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 (2014). A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems. CoRR. http://arxiv.org/abs/1404.0533

Kappes, J H, Savchynskyy, B and Schnörr, C (2012). A Bundle Approach To Efficient MAP-Inference by Lagrangian Relaxation. CVPR. Proceedings. 1688-1695

Kappes, J H, Schmidt, S and Schnörr, C (2010). MRF Inference by k-Fan Decomposition and Tight Lagrangian Relaxation. European Conference on Computer Vision (ECCV). Springer. 6313 735--747

Karim, R, Bergtholdt, M, Kappes, J H and Schnörr, C (2007). Greedy-Based Design of Sparse Two-Stage SVMs for Fast Classification. Pattern Recognition – 29th DAGM Symposium. Springer. 4713 395-404

Karim, R, Bergtholdt, M, Kappes, J H and Schnörr, C (2007). Greedy-Based Design of Sparse Two-Stage SVMs for Fast Classification. Pattern Recognition -- 29th DAGM Symposium. Springer. 4713 395-404

Technical Report (491.56 KB)

Kassemeyer, S (2009). Quantification Of Tumour Angiogenesis Using Pattern Recognition. University of Heidelberg

Kaster, F O (2011). Image Analysis for the Life Sciences - Computer-assisted Tumor Diagnostics and Digital Embryomics. University of Heidelberg

Kaster, F O, Kelm, B Michael, Zechmann, C M, Weber, M - A, Hamprecht, F A and Nix, O (2009). Classification of Spectroscopic Images in the DIROlab Environment. World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany. Springer. 25/V 252--255

Technical Report (145.73 KB)

Kaster, F O, Weber, M - A and Hamprecht, F A (2011). Comparative Validation of Graphical Models for Learning Tumor Segmentations from Noisy Manual Annotations. LNCS. Springer, Heidelberg. LNCS 6533 74-85

Technical Report (544.56 KB)

Kaster, F O, Kassemeyer, S, Merkel, B, Nix, O and Hamprecht, F A (2010). An object-oriented library for systematic training and comparison of classifiers for computer-assisted tumor diagnosis from MRSI measurements. Bildverarbeitung für die Medizin 2010 -- Algorithmen, Systeme, Anwendungen. Springer. 97-101

Technical Report (1.12 MB)

Kaster, F O, Merkel, B, Nix, O and Hamprecht, F A (2011). An object-oriented library for systematic training and comparison of classifiers for computer-assisted tumor diagnosis from MRSI measurements. Computer Science - Research and Development. 26 65-85

Technical Report (808.16 KB)

Kauppi, J P, Kandemir, M, Saarinen, V M, Hirvenkari, L, Parkkonen, L, Klami, A, Hari, R and Kaski, S (2015). Towards brain-activity-controlled information retrieval: Decoding image relevance from MEG signals. NeuroImage. 112 288-298

Technical Report (2.39 MB)

Kausler, B X (2013). Tracking-by-Assignment as a Probabilistic Graphical Model with Applications in Developmental Biology. University of Heidelberg

Kausler, B X (2010). Modeling Of Spectral Peaks For Mass-Spectrometry-Based Proteomics. Universities of Karlsruhe and Heidelberg

Kausler, B X, Schiegg, M, Andres, B, Lindner, M, Köthe, U, Leitte, H, Wittbrodt, J, Hufnagel, L and Hamprecht, F A (2012). A Discrete Chain Graph Model for 3d+t Cell Tracking with High Misdetection Robustness. ECCV 2012. Proceedings. 7574 144-157

Technical Report (809.07 KB)

Kawetzki, D (2018). Semantic Segmentation Of Urban Scenes Using Deep Learning. Heidelberg University

Kelm, B Michael (2007). Evaluation of Vector-Valued Clinical Image Data Using Probabilistic Graphical Models: Quantification and Pattern Recognition. University of Heidelberg

Technical Report (4.89 MB)

Kelm, B Michael, Kaster, F O, Henning, A, Weber, M - A, Bachert, P, Bösinger, P, Hamprecht, F A and Menze, B H (2011). Using Spatial Prior Knowledge in the Spectral Fitting of Magnetic Resonance Spectroscopic Images. NMR in Biomedicine. 25(1) 1-13

Technical Report (1.94 MB)

Kelm, B Michael, Müller, N, Menze, B H and Hamprecht, F A (2006). Bayesian Estimation of Smooth Parameter Maps for Dynamic Contrast-Enhanced MR Images with Block-ICM. Proc Computer Vision and Pattern Recognition Workshop (Mathematical Methods in Biomedical Image Analysis). IEEE Computer Society. 96-103

Technical Report (232.69 KB)

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