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2011

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.

Technical Report (672.68 KB)

C. Sommer, Straehle, C. N., Köthe, U., and Hamprecht, F. A., “ilastik: Interactive Learning and Segmentation Toolkit”, in Eighth IEEE International Symposium on Biomedical Imaging (ISBI 2011).Proceedings, 2011, pp. 230-233.

M. Frank and Hamprecht, F. A., “Image-Based Supervision of a Periodically Working Machine”, Pattern Analysis and Applications, pp. 1-10, 2011.

Technical Report (466.61 KB)

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

Technical Report (808.16 KB)

B. H. Menze, Kelm, B. Michael, Splitthoff, N., Köthe, U., and Hamprecht, F. A., “On oblique random forests”, in European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2011. Proceedings., 2011, pp. 453-469.

Technical Report (665.33 KB)

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.

Technical Report (8.18 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.

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.

M. Hanselmann, Voss, B., Renard, B. Y., Lindner, M., Köthe, U., Kirchner, M., and Hamprecht, F. A., “SIMA: Simultaneous Multiple Alignment of LC/MS Peak Lists”, Bioinformatics, vol. 27 (7), pp. 987-993, 2011.

Technical Report (2.2 MB)

X. Lou and Hamprecht, F. A., “Structured Learning for Cell Tracking”, in NIPS 2011. Proceedings, 2011, pp. 1296-1304.

Technical Report (1.41 MB)

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

Technical Report (1.94 MB)

M. Pfannmöller, Flügge, H., Benner, G., Wacker, I., Sommer, C., Hanselmann, M., Schmale, S., Schmidt, H., Hamprecht, F. A., Rabe, T., Kowalsky, W., and Schröder, R., “Visualizing a homogeneous blend in bulk heterojunction polymer solar cells by analytical electron microscopy”, Nano Letters, vol. 11, pp. 3099-3107, 2011.

2012

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

Technical Report (20.85 MB)

M. Hanselmann, Röder, J., Köthe, U., Renard, B. Y., Heeren, R. M. A., and Hamprecht, F. A., “Active Learning for Convenient Annotation and Classification of Secondary Ion Mass Spectrometry Images”, Analytical Chemistry, vol. 85 (1), pp. 147-155, 2012.

Technical Report (2.58 MB)

J. Röder, Kunzmann, K., Nadler, B., and Hamprecht, F. A., “Active Learning with Distributional Estimates”, UAI 2012. Proceedings, pp. 715-725, 2012.

Technical Report (267.67 KB)

C. M. Zechmann, Menze, B. H., Kelm, B. Michael, Zamecnik, P., Ikinger, U., Waldherr, R., Delorme, S., Hamprecht, F. A., and Bachert, P., “Automated vs. manual pattern recognition of 3D 1H MRSI data of patients with prostate cancer”, Academic Radiology, vol. 19, 6, pp. 675-684, 2012.

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

Technical Report (809.07 KB)

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.

Technical Report (1.64 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.

Technical Report (2.72 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.

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.

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.

L. Fiaschi, Nair, R., Köthe, U., and Hamprecht, F. A., “Learning to Count with Regression Forest and Structured Labels”, ICPR 2012. Proceedings, pp. 2685-2688, 2012.

Technical Report (3.66 MB)

X. Lou and Hamprecht, F. A., “Learning to Segment Dense Cell Nuclei with Shape Prior”, CVPR 2012. Proceedings, pp. 1012-1018, 2012.

Technical Report (2.66 MB)

C. Sommer, Fiaschi, L., Hamprecht, F. A., and Gerlich, D., “Learning-based Mitotic Cell Detection in Histopathological Images”, ICPR 2012. Proceedings, pp. 2306-2309, 2012.

Technical Report (1.96 MB)

E. - A. Horvát, Hanselmann, M., Hamprecht, F. A., and Zweig, K. A., “One plus one makes three (for social networks)”, PLoS ONE, vol. 4,7, 2012.

B. Y. Renard, Xu, B., Kirchner, M., Zickmann, F., Winter, D., Korten, S., Brattig, N., Tzur, A., Hamprecht, F. A., and Steen, H., “Overcoming species boundaries in peptide identification with BICEPS”, Molecular and Cellular Proteomics, vol. 11, 2012.

Technical Report (444.6 KB)

X. Lou, Fiaschi, L., Köthe, U., and Hamprecht, F. A., “Quality Classification of Microscopic Imagery with Weakly Supervised Learning”, MICCAI-MLMI. Proceedings, pp. 176-183, 2012.

Technical Report (4.15 MB)

C. N. Straehle, Köthe, U., Briggman, K., Denk, W., and Hamprecht, F. A., “Seeded watershed cut uncertainty estimators for guided interactive segmentation”, in CVPR 2012. Proceedings, 2012, pp. 765 - 772.

Technical Report (2.84 MB)

X. Lou and Hamprecht, F. A., “Structured Learning from Partial Annotations”, ICML 2012. Proceedings, 2012.

Technical Report (843.45 KB)

E. - A. Horvát, Hanselmann, M., Hamprecht, F. A., and Zweig, K. A., “You Are Who Knows You: Predicting Links Between Non-Members of Facebook”, European Conference on Complex Systems. Proceedings, vol. 3, pp. 309-315, 2012.

Technical Report (1.92 MB)

2013

F. Diego, Reichinnek, S., Both, M., and Hamprecht, F. A., “Automated Identification of Neuronal Activity from Calcium Imaging by Sparse Dictionary Learning”, ISBI 2013. Proceedings, pp. 1058-1061, 2013.

Technical Report (2.82 MB)

R. Mikut, Dickmeis, T., Driever, W., Geurts, P., Hamprecht, F. A., Kausler, B. X., Ledesma-Carbayo, M., Marée, R., Mikula, K., Pantazis, P., Ronneberger, O., Santos, A., and Stotzka, R., “Automated Processing of Zebrafish Imaging Data: A Survey”, Zebrafish, vol. 10 (3), 2013.

Technical Report (1.73 MB)

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

Technical Report (1.35 MB)

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

Technical Report (1.35 MB)

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