Publications

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Journal Article
M. Frank and Hamprecht, F. A., Image-Based Supervision of a Periodically Working Machine, Pattern Analysis and Applications, pp. 1-10, 2011.PDF icon Technical Report (466.61 KB)
S. Wolf, Hamprecht, F. A., and Funke, J., Instance Separation Emerges from Inpainting, arXiv preprint arXiv:2003.00891, 2020.
S. I. Friman and Jähne, B., Investigating SO2 transfer across the air–water interface via LIF, Exp. Fluids, vol. 60, p. 65, 2019.
B. Jähne, Libner, P., Fischer, R., Billen, T., and Plate, E. J., Investigating the transfer process across the free aqueous boundary layer by the controlled flux method, Tellus, vol. 41B, p. 177--195, 1989.
L. Fiaschi, Grosser, K. - H., Afonso, B., Zlatic, M., and Hamprecht, F. A., Keeping Count: Leveraging Temporal Context to Count Heavily Overlapping Objects, ISBI 2013.Proceedings, pp. 656-659, 2013.PDF icon Technical Report (711.68 KB)
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.PDF icon Technical Report (3.66 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.PDF icon Technical Report (1.96 MB)
J. Fehr, Local Rotation Invariant Patch Descriptors for 3D Vector Fields, Pattern Recognition, International Conference on, Istanbul, Turkey, August 23-26, 2010, pp. 1381-1384, 2010.
W. Erb, Weinmann, A., Ahlborg, M., Brandt, C., Bringout, G., Buzug, T. M., Frikel, J., Kaethner, C., Knopp, T., März, T., Möddel, M., Storath, M., and Weber, A., Mathematical Analysis of the 1D Model and Reconstruction Schemes for Magnetic Particle Imaging, Inverse Problems, vol. 34, no. 5, 2018.
M. Welk, Weickert, J., Becker, F., Schnörr, C., Feddern, C., and Burgeth, B., Median and related local filters for tensor-valued images, Signal Processing, vol. 87, pp. 291-308, 2007.PDF icon Technical Report (1007.29 KB)
M. Welk, Weickert, J., Becker, F., Schnörr, C., Feddern, C., and Burgeth, B., Median and related local filters for tensor-valued images, Signal Processing, vol. 87, pp. 291-308, 2007.
D. Uttenweiler, Veigel, C., Steubing, R., Götz, C., Mann, S., Haußecker, H., Jähne, B., and Fink, R. H. A., Motion determination in actin filament fluorescence images with a spatio-temporal orientation analysis method., Biophys J, vol. 78, p. 2709--2715, 2000.
F. Friedl, Krah, N., and Jähne, B., Optical sensing of oxygen using a modified Stern-Volmer equation for high laser irradiance, Sensors and Actuators B: Chemical, vol. 206, p. 336--342, 2015.
F. Friedl, Krah, N., and Jähne, B., Optical sensing of oxygen using a modified Stern-Volmer equation for high laser irradiance, Sensors and Actuators B: Chemical, vol. 206, pp. 336–342, 2015.
F. Jug, Pietzsch, T., Kainmüller, D., Funke, J., Kaiser, M., van Nimwegen, E., Rother, C., and Myers, G., Optimal joint segmentation and tracking of escherichia coli in the mother machine, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8677, pp. 25–36, 2014.
F. Besse, Rother, C., Fitzgibbon, A., and Kautz, J., PMBP: PatchMatch Belief Propagation for correspondence field estimation, International Journal of Computer Vision, vol. 110, pp. 2–13, 2014.
F. Besse, Rother, C., Fitzgibbon, A., and Kautz, J., PMBP: PatchMatch Belief Propagation for correspondence field estimation, International Journal of Computer Vision, vol. 110, pp. 2–13, 2014.
F. Besse, Rother, C., Fitzgibbon, A., and Kautz, J., PMBP: PatchMatch Belief Propagation for correspondence field estimation, International Journal of Computer Vision, vol. 110, pp. 2–13, 2014.
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.PDF icon Technical Report (4.15 MB)
D. Uttenweiler, Weber, C., Jähne, B., Fink, R. H. A., and Schaar, H., Spatiotemporal anisotropic diffusion filtering to improve signal-to-noise ratios and object restoration in fluorescence microscopic image sequences., J Biomed Opt, vol. 8, p. 40--47, 2003.
M. Frank, Plaue, M., Rapp, H., Köthe, U., Jähne, B., and Hamprecht, F. A., Theoretical and Experimental Error Analysis of Continuous-Wave Time-Of-Flight Range Cameras, Optical Engineering, vol. 48, 013602, 2009.PDF icon Technical Report (2.03 MB)
M. Frank, Plaue, M., Rapp, H., Köthe, U., Jähne, B., and Hamprecht, F. A., Theoretical and experimental error analysis of continuous-wave time-of-flight range cameras, Opt. Eng., vol. 48, p. 013602, 2009.
H. Rapp, Frank, M., Hamprecht, F. A., and Jähne, B., A Theoretical and Experimental Investigation of the Systematic Errors and Statistical Uncertainties of Time-of-Flight Cameras, Int. J. Intelligent Systems Technologies and Applications, vol. 5, pp. 402-413, 2008.PDF icon Technical Report (798.23 KB)
H. Rapp, Frank, M., Hamprecht, F. A., and Jähne, B., A theoretical and experimental investigation of the systematic errors and statistical uncertainties of time-of-flight cameras, Int. J. Intelligent Systems Technologies and Applications, vol. 5, p. 402--413, 2008.
B. Brattoli, Büchler, U., Dorkenwald, M., Reiser, P., Filli, L., Helmchen, F., Wahl, A. - S., and Ommer, B., Unsupervised behaviour analysis and magnification (uBAM) using deep learning, Nature Machine Intelligence, 2021.
A. Bruhn, Weickert, J., Feddern, C., Kohlberger, T., and Schnörr, C., Variational optic flow computation in real-time, IEEE Trans. Image Proc., vol. 14, pp. 608–615, 2005.
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.

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