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Author Title [ Type(Desc)] Year
Filters: Author is Thorsten Beier  [Clear All Filters]
Conference Paper
T. Kröger, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., “Asymmetric Cuts: Joint Image Labeling and Partitioning”, in Pattern Recognition - 36th German Conference, {GCPR} 2014, Münster, Germany, September 2-5, 2014, Proceedings, 2014.PDF icon Technical Report (3.46 MB)
T. Kröger, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., “Asymmetric Cuts: Joint Image Labeling and Partitioning”, in 36th German Conference on Pattern Recognition, 2014.
T. Beier, Kröger, T., Kappes, J. H., Köthe, U., and Hamprecht, F. A., “Cut, Glue and Cut: A Fast, Approximate Solver for Multicut Partitioning”, in 2014 {IEEE} Conference on Computer Vision and Pattern Recognition, {CVPR} 2014, Columbus, OH, USA, June 23-28, 2014, 2014.PDF icon Technical Report (10.06 MB)
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)
N. Krasowski, Beier, T., Knott, G. W., Köthe, U., Hamprecht, F. A., and Kreshuk, A., “Improving 3D EM Data Segmentation by Joint Optimization over Boundary Evidence and Biological Priors”, in 12th {IEEE} International Symposium on Biomedical Imaging, {ISBI} 2015, Brooklyn, NY, USA, April 16-19, 2015, 2015, pp. 536-539.PDF icon Technical Report (2.25 MB)
B. Andres, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., “The Lazy Flipper: Efficient Depth-Limited Exhaustive Search in Discrete Graphical Models”, in Computer Vision - {ECCV} 2012 - 12th European Conference on Computer Vision, Florence, Italy, October 7-13, 2012, Proceedings, Part {VII}, 2012.PDF icon Technical Report (446.28 KB)
B. Andres, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., “The Lazy Flipper: Efficient Depth-limited Exhaustive Search in Discrete Graphical Models”, in ECCV 2012, 2012.PDF icon Technical Report (532.64 KB)
B. Andres, Kappes, J. Hendrik, Beier, T., Köthe, U., and Hamprecht, F. A., “The Lazy Flipper: Efficient Depth-limited Exhaustive Search in Discrete Graphical Models”, in ECCV 2012, 2012.
J. H. Kappes, Beier, T., and Schnörr, C., “MAP-Inference on Large Scale Higher-Order Discrete Graphical Models by Fusion Moves”, in Computer Vision - {ECCV} 2014 Workshops - Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part {II}, 2014.PDF icon Technical Report (557.49 KB)
J. Hendrik Kappes, Beier, T., and Schnörr, C., “MAP-Inference on Large Scale Higher-Order Discrete Graphical Models by Fusion Moves”, in International Workshop on Graphical Models in Computer Vision, 2014.
J. Yarkony, Beier, T., Baldi, P., and Hamprecht, F. A., “Parallel Multicut Segmentation via Dual Decomposition”, in New Frontiers in Mining Complex Patterns - Third International Workshop, {NFMCP} 2014, Held in Conjunction with {ECML-PKDD} 2014, Nancy, France, September 19, 2014, Revised Selected Papers, 2014.
B. Andres, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., “Probabilistic Image Segmentation with Closedness Constraints”, in Proceedings of ICCV, 2011.PDF icon Technical Report (2.95 MB)
B. Andres, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., “Probabilistic Image Segmentation with Closedness Constraints”, in Proceedings of ICCV, 2011.
B. Andres, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., “Probabilistic Image Segmentation with Closedness Constraints”, in ICCV, Proceedings, 2011, pp. 2611 - 2618.PDF icon Technical Report (8.18 MB)
Conference Proceedings
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)
inproceedings
C. Pape, Beier, T., Li, P., Jain, V., Brock, D. D., and Kreshuk, A., “Solving Large Multicut Problems for Connectomics via Domain Decomposition”, Bioimage Computing Workshop. ICCV. pp. 1-10, 2017.
Journal Article
S. Berg, Kutra, D., Kroeger, T., Straehle, C. N., Kausler, B. X., Haubold, C., Schiegg, M., Ales, J., Beier, T., Rudy, M., Eren, K., Cervantes, J. I., Xu, B., Beuttenmüller, F., Wolny, A., Zhang, C., Köthe, U., Hamprecht, F. A., and Kreshuk, A., “ilastik: interactive machine learning for (bio)image analysis”, Nature Methods, vol. 16, pp. 1226-1232, 2019.
T. Beier, Pape, C., Rahaman, N., Prange, T., Berg, S., Bock, D., Cardona, A., Knott, G. W., Plaza, S. M., Scheffer, L. K., Köthe, U., Kreshuk, A., and Hamprecht, F. A., “Multicut brings automated neurite segmentation closer to human performance”, Nature Methods, vol. 14, no. 2, pp. 101-102, 2017.
N. Krasowki, Beier, T., Knott, G. W., Köthe, U., Hamprecht, F. A., and Kreshuk, A., “Neuron Segmentation with High-Level Biological Priors”, IEEE Transactions on Medical Imaging, vol. 37, no. 4, 2017.
B. Andres, Beier, T., and Kappes, J. H., “OpenGM: A C++ Library for Discrete Graphical Models”, ArXiv e-prints, 2012.
Masters Thesis
T. Beier, “Graph based image analysis”, University of Heidelberg, 2014.
PhD Thesis
T. Beier, “Multicut Algorithms for Neurite Segmentation”. Heidelberg University, 2018.