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In Collection

H. Eisele and Hamprecht, F. A., “A new approach for defect detection in X-ray CT images”, Pattern Recognition, vol. 2449. Springer, pp. 345-352, 2003.

Technical Report (398.88 KB)

X. Lou, Kloft, M., Rätsch, G., and Hamprecht, F. A., “Structured Learning from Cheap Data”, Advanced Structured Prediction. The MIT Press, 2014.

Technical Report (8.35 MB)

S. Hader and Hamprecht, F. A., “Two-Stage Classification with Automatic Feature Selection for an Industrial Application”, Classification, the ubiquitous challenge: Proceedings of GfKl 2004. Springer, pp. 137-144, 2004.

Technical Report (518.16 KB)

inproceedings

M. Kandemir, Feuchtinger, A., Walch, A., and Hamprecht, F. A., “Digital Pathology: Multiple instance learning can detect Barrett'scancer”, ISBI. Proceedings. pp. 1348-1351, 2014.

Technical Report (2.86 MB)

S. Wolf, Schott, L., Köthe, U., and Hamprecht, F. A., “Learned Watershed: End-to-End Learning of Seeded Segmentation”, ICCV. pp. 2030-2038, 2017.

Technical Report (3.76 MB)

Journal Article

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)

M. Kandemir, Hamprecht, F. A., Wojek, C., and Schmidt, U., “Active machine learning for training an event classification”, Patent, Patent Number WO2017032775 A1, 2017.

X. Lou, Schiegg, M., and Hamprecht, F. A., “Active Structured Learning for Cell Tracking: Algorithm, Framework and Usability”, IEEE Transactions on Medical Imaging, vol. 33 (4), pp. 849-860, 2014.

Technical Report (6.84 MB)

L. Görlitz, Hamprecht, F. A., and Staudacher, M., “Allocation of particles to development processes”, Patent, 2009.

Technical Report (406.7 KB)

M. Kirchner, Saussen, B., Steen, H., Steen, J. A. J., and Hamprecht, F. A., “amsrpm: Robust Point Matching in Retention Time Alignment of LC/MS Data with R”, Journal of Statistical Software, vol. 18, pp. 1-12, 2007.

M. Hayn, Beirle, S., Hamprecht, F. A., Platt, U., Menze, B. H., and Wagner, T., “Analysing spatio-temporal patterns of the global NO₂-distribution retrieved frome GOME satellite observations using a generalized additive model”, Atmospheric Chemistry and Physics, vol. 9, pp. 9367-9398, 2009.

Technical Report (2.52 MB)

M. Jäger, Kiel, A., Herten, D. - P., and Hamprecht, F. A., “Analysis of Single-Molecule Fluorescence Spectroscopic Data with a Markov Modulated Poisson Process”, ChemPhysChem, vol. 10:14, pp. 2486-2495, 2009.

A. Kreshuk, Stankiewicz, M., Lou, X., Kirchner, M., Hamprecht, F. A., and Mayer, M. P., “Automated detection and analysis of bimodal isotope peak distribution in H/D exchange mass spectrometry using HeXicon”, International Journal of Mass Spectrometry, vol. 302, pp. 125-131, 2010.

Technical Report (3.22 MB)

A. Kreshuk, Straehle, C. N., Sommer, C., Köthe, U., Cantoni, M., Knott, G. W., and Hamprecht, F. A., “Automated Detection and Segmentation of Synaptic Contacts in Nearly Isotropic Serial Electron Microscopy Images”, PLoS ONE, vol. 6 (10), 2011.

Technical Report (290.48 KB)

A. Kreshuk, Köthe, U., Pax, E., Bock, D. D., and Hamprecht, F. A., “Automated Detection of Synapses in Serial Section Transmission Electron Microscopy Image Stacks”, PLoS ONE, vol. 9, p. 2, 2014.

Technical Report (16.66 MB)

B. Michael Kelm, Menze, B. H., Zechmann, C. M., Baudendistel, K. T., and Hamprecht, F. A., “Automated Estimation of Tumor Probability in Prostate MRSI: Pattern Recognition vs. Quantification”, Magnetic Resonance in Medicine, vol. 57, pp. 150-159, 2007.

Technical Report (348.05 KB)

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)

A. Kreshuk, Walecki, R., Köthe, U., Gierthmühlen, M., Plachta, D., Genoud, C., Haastert-Talini, K., and Hamprecht, F. A., “Automated Tracing of Myelinated Axons and Detection of the Nodes of Ranvier in Serial Images of Peripheral Nerves”, Journal of Microscopy, vol. 259 (2), pp. 143-154, 2015.

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.

M. Hissmann and Hamprecht, F. A., “Bayesian surface estimation for white light interferometry”, Optical Engineering, vol. 44, pp. 1-9, 2005.

Technical Report (549.46 KB)

F. A. Hamprecht, Thiel, W., and van Gunsteren, W. F., “Chemical library subset selection algorithms: a unified derivation using spatial statistics”, Journal of Chemical Information and Computer Sciences, vol. 42, pp. 414-428, 2002.

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

Technical Report (1.5 MB)

J. H. Kappes, 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., “A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems”, CoRR, 2014.

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

Technical Report (5.12 MB)

J. H. Kappes, 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., “A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems”, CoRR, vol. abs/1404.0533, 2014.

Technical Report (3.32 MB)

J. H. Kappes, 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., “A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems”, International Journal of Computer Vision, vol. 115, pp. 155–184, 2015.

J. H. Kappes, 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., “A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems”, International Journal of Computer Vision, vol. 115, pp. 155–184, 2015.

J. H. Kappes, 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., “A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems”, International Journal of Computer Vision, vol. 115, pp. 155–184, 2015.

C. Weber, Zechmann, C. M., Kelm, B. Michael, Zamecnik, R., Hendricks, D., Waldherr, R., Hamprecht, F. A., Delorme, S., Bachert, P., and Ikinger, U., “Comparison of correctness of manuel and automatic evaluation of MR-spectrum with prostrate cancer”, Der Urologe, vol. 46, p. 1252, 2007.

B. H. Menze, Kelm, B. Michael, Masuch, R., Himmelreich, U., Bachert, P., Petrich, W., and Hamprecht, F. A., “A Comparison of Random Forest and its Gini Importance with Standard Chemometric Methods for the Feature Selection and Classification of Spectral Data”, BMC Bioinformatics, vol. 10:213, 2009.

Technical Report (675 KB)

M. Kirchner, Renard, B. Y., Köthe, U., Pappin, D. J., Hamprecht, F. A., Steen, J. A. J., and Steen, H., “Computational Protein Profile Similarity Screening for Quantitative Mass Spectrometry Experiments”, Bioinformatics, vol. 26 (1), pp. 77-83, 2010.

Technical Report (380.19 KB)

M. Kandemir and Hamprecht, F. A., “Computer-aided diagnosis from weak supervision: A benchmarking study”, Computerized Medical Imaging and Graphics, vol. 42, pp. 44-50, 2014.

Technical Report (4.28 MB)

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