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

 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

 Kröger, T, Kappes, J H, Beier, T, Köthe, U and Hamprecht, F A (2014). Asymmetric Cuts: Joint Image Labeling and Partitioning. Pattern Recognition - 36th German Conference, {GCPR} 2014, Münster, Germany, September 2-5, 2014, Proceedings. http://dx.doi.org/10.1007/978-3-319-11752-2_16

 Tek, B F, Kröger, T, Mikula, S and Hamprecht, F A (2014). Automated Cell Nucleus Detection for Large-Volume Electron Microscopy of Neural Tissue. ISBI. Proceedings. 69-72

 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 StructuredDiscrete Energy Minimization Problems. CoRR. http://arxiv.org/abs/1404.0533

 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/

 Beier, T, Kröger, T, Kappes, J H, Köthe, U and Hamprecht, F A (2014). Cut, Glue and Cut: A Fast, Approximate Solver for Multicut Partitioning. 2014 {IEEE} Conference on Computer Vision and Pattern Recognition, {CVPR} 2014, Columbus, OH, USA, June 23-28, 2014. http://dx.doi.org/10.1109/CVPR.2014.17

 Kröger,  (2014). Learning-based Segmentation for Connectomics. University of Heidelberg

 Kröger, T, Mikula, S, Denk, W, Köthe, U and Hamprecht, F A (2013). Learning to Segment Neurons with Non-local Quality Measures. MICCAI 2013. Proceedings, part II. Springer. 8150 419-427

 Andres, B, Köthe, U, Kröger, T, Helmstaedter, M, Briggmann, K L, Denk, W and Hamprecht, F A (2012). 3D Segmentation of SBFSEM Images of Neuropil by a Graphical Model over Supervoxel Boundaries. Medical Image Analysis. 16 (2012) 796-805

 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. 778-791

 Monroy, A, Kröger, T, Arnold, M and Ommer, B (2011). Parametric Object Detection for Iconographic Analysis. Scientific Computing & Cultural Heritage. http://www.academia.edu/9439693/Parametric_Object_Detection_for_Iconographic_Analysis

 Kröger,  (2010). Exploratory And Computational Analysis Of Huge Volume Images For Connectomics. University of Heidelberg

 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). 22-26

 Andres, B, Köthe, U, Kröger, T and Hamprecht, F A (2010). How to Extract the Geometry and Topology from Very Large 3D Segmentations. ArXiv e-prints. http://arxiv.org/abs/1009.6215

 Andres, B, Köthe, U, Kröger, T and Hamprecht, F A (2010). Runtime-Flexible Multi-dimensional Views and Arrays for C++98 and C++0x. ArXiv e-prints. http://arxiv.org/abs/1008.2909v1