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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)

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)

F. A. Hamprecht, “Classification”, Practical Handbook on Image Processing for Scientific and Technical Applications. CRC Press, pp. 509-519, 2004.

Technical Report (320.84 KB)

F. A. Hamprecht, Achleitner, U., Krismer, A. C., Lindner, K. H., Wenzel, V., Strohmenger, H. - U., Thiel, W., and van Gunsteren, W. F., “Fibrillation power: An alternative method of ECG spectral analysis for prediction of countershock success in a porcine model of ventricular fibrillation”, Resuscitation, vol. 50, pp. 287-296, 2001.

F. A. Hamprecht, Cohen, A. J., Tozer, D. J., and Handy, N. C., “Development and assessment of new exchange-correlation functionals”, Journal of Chemical Physics, vol. 109, pp. 6264-6271, 1998.

F. A. Hamprecht and Jähne, B., “Vom Bild zur Information”, Ruperto Carola -- Forschungsmagazin der Universität Heidelberg, vol. 03.2004, pp. 9-12, 2004.

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.

F. A. Hamprecht, Peter, C., Daura, X., Thiel, W., and van Gunsteren, W. F., “A strategy for analysis of (molecular) equilibrium simulations: configuration space density estimation, clustering and visualization”, Journal of Chemical Physics, vol. 114, pp. 2079-2089, 2001.

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.

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.

F. A. Hamprecht and Agrell, E., “Exploring a space of materials: spatial sampling design and subset selection”, Experimental Design for Combinatorial and High Throughput Materials Development. Wiley, 2003.

Technical Report (2.28 MB)

F. A. Hamprecht, Scott, W. R. P., and van Gunsteren, W. F., “Generation of pseudo-native protein structures for threading”, Proteins, vol. 28, pp. 522-529, 1997.

F. A. Hamprecht and Jähne, B., “Vom Bild zur Information”. 2004.

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

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

C. Haltebourg, “Modeling of Heat Exchange Across the Ocean Surface as Measured by Active Thermography”, vol. Dissertation. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ. Heidelberg, 2017.

D. Halsema, Jähne, B., Calkoen, C. J., and Snoeij, P., “First results of the VIERS-1 experiment”, in Radar Scattering from Modulated Wind Waves, W. A. Oost, Komen, G. J., and Oost, W. A., Eds. Kluwer Academic Publishers, 1989, p. 49--57.

A. Haller, “Interactive Watershed Based Segmentation for Biological Images”, University of Heidelberg, 2017.

S. Haller, Prakash, M., Hutschenreiter, L., Pietzsch, T., Rother, C., Jug, F., Swoboda, P., and Savchynskyy, B., “A Primal-Dual Solver for Large-Scale Tracking-by-Assignment”, AISTATS 2020. 2020.

PDF (1.04 MB)

S. Haller, Swoboda, P., and Savchynskyy, B., “Exact MAP-Inference by Confining Combinatorial Search With LP Relaxation”, in Thirty-Second AAAI Conference on Artificial Intelligence, (AAAI-18), New Orleans, Louisiana, USA, February 2-7, 2018, 2018.

2018-02-02_aaai_dense_combilp.pdf (325.08 KB)

A. Haja, “Graph-based Spatial Motion Tracking using Affine-covariant Regions”. IWR, Fakultät für Mathematik und Informatik, Univ.\ Heidelberg, 2008.

A. Haja, Abraham, S., and Jähne, B., “A Comparison of Region Detectors for Tracking”, in Pattern Recognition, Proceedings 30th DAGM Symposium, Munich, Germany, June 2008, 2008, vol. 5096, p. 112--121.

A. Haja, Jähne, B., and Abraham, S., “Localization accuracy of region detectors”, in Proceedings CVPR'08, 2008.

R. Haeusler, Nair, R., and Kondermann, D., “Ensemble Learning for Confidence Measures in Stereo Vision”, in CVPR 2013, in press, 2013, pp. 305-312.

S. Hader, “Data Mining auf multidimensionalen und komplexen Daten in der industriellen Bildverarbeitung”. University of Heidelberg, 2006.

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)

S. Hader, “System Concept for Image Sequence Classification in Laser Welding”, Pattern Recognition, vol. 2781. Springer, pp. 212-219, 2003.

S. Hader and Hamprecht, F. A., “Efficient Density Clustering”, Between Data Science and Applied Data Analysis. Springer, pp. 39-48, 2003.

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