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M

C. N. Straehle, Kandemir, M., Köthe, U., and Hamprecht, F. A., “Multiple instance learning with response-optimized random forests”, in ICPR. Proceedings, 2014, pp. 3768 - 3773.

Technical Report (296.66 KB)

B. H. Menze, Petrich, W., and Hamprecht, F. A., “Multivariate feature selection and hierarchical classification for infrared spectroscopy: serum-based detection of bovine spongiform encephalopathy”, Analytical and Bioanalytical Chemistry, vol. 387, pp. 1801-1807, 2007.

Technical Report (283.47 KB)

M. Hanselmann, Köthe, U., Renard, B. Y., Kirchner, M., Heeren, R. M. A., and Hamprecht, F. A., “Multivariate Watershed Segmentation of Compositional Data”, in Proceedings of the 15th International Conference on Discrete Geometry for Computer Imagery (DGCI), in press, 2009, vol. 5810, pp. 180-192.

Technical Report (1.25 MB)

S. Wolf, Pape, C., Bailoni, A., Rahaman, N., Kreshuk, A., Köthe, U., and Hamprecht, F. A., “The Mutex Watershed: Efficient, Parameter-Free Image Partitioning”, ECCV. Proceedings. Springer, pp. 571-587, 2018.

S. Wolf, Pape, C., Bailoni, A., Rahaman, N., Kreshuk, A., Köthe, U., and Hamprecht, F. A., “The Mutex Watershed: Efficient, Parameter-Free Image Partitioning”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2018, vol. 11208 LNCS, pp. 571–587.

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S. Trittler and Hamprecht, F. A., “Near-Optimum Sampling Design and an Efficient Algorithm for Single Tone Frequency Estimation”, Digital Signal Processing, vol. 19, pp. 628-639, 2009.

Technical Report (511.23 KB)

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.

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)

B. Y. Renard, Kirchner, M., Steen, H., Steen, J. A. J., and Hamprecht, F. A., “NITPICK: Peak Identification for Mass Spectrometry Data”, BMC Bioinformatics, vol. 9, p. 355, 2008.

Technical Report (643.89 KB)

J. Restle, Hissmann, M., and Hamprecht, F. A., “Nonparametric Smoothing of Height maps using ``Confidence'' values”, Optical Engineering, vol. 43, pp. 866-871, 2004.

Technical Report (1.07 MB)

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V. Ulman, Maška, M., Magnusson, K. E. G., Ronneberger, O., Haubold, C., Harder, N., Matula, P., Matula, P., Svoboda, D., Radojevic, M., Smal, I., Rohr, K., Jaldén, J., Blau, H. M., Dzyubachyk, O., Lelieveldt, B., Xiao, P., Li, Y., Cho, S. - Y., Dufour, A., Olivo-Marin, J. C., Reyes-Aldasoro, C. C., Solis-Lemus, J. A., Bensch, R., Brox, T., Stegmaier, J., Mikut, R., Wolf, S., Hamprecht, F. A., Esteves, T., Quelhas, P., Demirel, Ö., Malström, L., Jug, F., Tomančák, P., Meijering, E., Muñoz-Barrutia, A., Kozubek, M., and Ortiz-de-Solorzano, C., “An Objective Comparison of Cell Tracking Algorithms”, Nature Methods, vol. 14, no. 12, pp. 1141-1152, 2017.

Technical Report (4.24 MB)

F. O. Kaster, Kassemeyer, S., 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”, in Bildverarbeitung für die Medizin 2010 -- Algorithmen, Systeme, Anwendungen, 2010, pp. 97-101.

Technical Report (1.12 MB)

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)

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. H. Menze, Lichy, M. P., Bachert, P., Kelm, B. Michael, Schlemmer, H. P., and Hamprecht, F. A., “Optimal Classification of Long Echo Time in vivo Magnetic Resonance Spectra in the Detection of Recurrent Brain Tumor”, NMR in Biomedicine, vol. 19, pp. 599-609, 2006.

Technical Report (289.77 KB)

H. R. Künsch, Agrell, E., and Hamprecht, F. A., “Optimal lattices for sampling”, IEEE Transactions on Information Theory, vol. 51, pp. 634-647, 2005.

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)

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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.

F. A. Hamprecht, Schnörr, C., and Jähne, B., Eds., “Pattern Recognition – 29th DAGM Symposium”, LCNS, vol. 4713. Springer, 2007.

F. A. Hamprecht, Jähne, B., and Schnörr, C., Eds., Pattern Recognition, 29th DAGM Symposium, Heidelberg, Germany, September 12-14, 2007, Proceedings, vol. 4713. Springer, 2007.

C. Schnörr and Jähne, B., “Pattern Recognition, 29th DAGM Symposium, Heidelberg, Germany, September 12-14”, vol. 4713. Springer, 2007.

F. A. Hamprecht, Jost, D., Rüttimann, M., Calamai, F., and Kowalski, J. J., “Preliminary results on the prediction of countershock success with fibrillation power”, Resuscitation, vol. 50, pp. 297-299, 2001.

M. Jäger and Hamprecht, F. A., “Principal Component Imagery for the Quality Monitoring of Dynamic Laser Welding Processes”, IEEE Transactions on Industrial Electronics, vol. 56:4, pp. 1307-1313, 2008.

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.

L. Görlitz, Menze, B. H., Kelm, B. Michael, and Hamprecht, F. A., “Processing Spectral Data”, Surface and Interface Analysis, vol. 41, pp. 636-644, 2009.

Technical Report (4.17 MB)

M. Schiegg, Heuer, B., Haubold, C., Wolf, S., Köthe, U., and Hamprecht, F. A., “Proof-reading Guidance in Cell Tracking by Sampling from Tracking-by-assignment Models”, in ISBI. Proceedings, 2015, pp. 394-398.

Technical Report (648.55 KB)

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S. Sieg, Stutz, B., Schmidt, T., Hamprecht, F. A., and Maier, W. F., “A QCAR-approach to materials modelling”, Journal of Molecular Modeling, vol. 12, pp. 611-619, 2006.

Technical Report (343.11 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)

B. Andres, Köthe, U., Bonea, A., Nadler, B., and Hamprecht, F. A., “Quantitative Assessment of Image Segmentation Quality by Random Walk Relaxation Times”, in Pattern Recognition. 31st DAGM Symposium, Jena, Germany, September 9-11, 2009. Proceedings, 2009, vol. 5748, pp. 502-511.

Technical Report (3.08 MB)

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H. Zhang, Hamprecht, F. A., and Amann, A., “Report about VOCs Dataset's Analysis based on Random Forests”, in Proceedings of the HPC-Asia05, 2005, pp. 603-607.

Technical Report (232.13 KB)

T. König, Menze, B. H., Kirchner, M., Monigatti, F., Parker, K. C., Patterson, T., Steen, J. J., Hamprecht, F. A., and Steen, H., “Robust Prediction of the MASCOT Score for an Improved Quality Assessment in Mass Spectrometric Proteomics”, Journal of Proteome Research, vol. 7, pp. 3708-3717, 2008.

Technical Report (1.16 MB)

B. Andres, Köthe, U., Kröger, T., and Hamprecht, F. A., “Runtime-Flexible Multi-dimensional Views and Arrays for C++98 and C++0x”, ArXiv e-prints, 2010.

Technical Report (415.54 KB)

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