Publications

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Reinecke, H (1997). Methoden Zur Bearbeitung Und Merkmalsextrahierung Von Zeitreihen Aus Technischen Anlagen. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg
Rathore, D (2016). Semantic Segmentation Using Deep Learning. University of Heidelberg
Rathke, F, Schmidt, S and Schnörr, C (2014). Probabilistic Intra-Retinal Layer Segmentation in 3-D OCT Images Using Global Shape Regularization. Med. Image Anal. 18 781–794
Rathke, F and Schnörr, C (2015). A Computational Approach to Log-Concave Density Estimation. An. St. Univ. Ovidius Constanta. 23 151-166PDF icon Technical Report (1.07 MB)
Rathke, F and Schnörr, C (2018). Fast Multivariate Log-Concave Density Estimation. preprint: ArXiv. https://arxiv.org/pdf/1805.07272.pdfPDF icon Technical Report (3.54 MB)
Rathke, F, Schmidt, S and Schnörr, C (2011). Order preserving and shape prior constrained intra-retinal layer segmentation in optical coherence tomography. Medical Image Computing and Computer-Assisted Intervention (MICCAI 2011). Springer. 6893 370–377
Rathke, F, Desana, M and Schnörr, C (2017). Locally Adaptive Probabilistic Models for Global Segmentation of Pathological OCT Scans. MICCAI. Proceedings. 177-184PDF icon Technical Report (4.79 MB)
Rathke, F, Schmidt, S and Schnörr, C (2011). Order Preserving and Shape Prior Constrained Intra-Retinal Layer Segmentation in Optical Coherence Tomography. MICCAI. Springer. 6893 370--377PDF icon Technical Report (1.12 MB)
Rathke, F, Hansen, K, Brefeld, U and Müller, K - R (2010). StructRank: A new approach for ligand-based virtual screening. J. Chem. Inf. Model. 51 83–92
Rathke, F, Schmidt, S and Schnörr, C (2014). Probabilistic Intra-Retinal Layer Segmentation in 3-D OCT Images Using Global Shape Regularization. Medical Image Analysis. 18 781-794PDF icon Technical Report (4.07 MB)
Rathke, F (2015). Probabilistic Graphical Models for Medical Image Segmentation. University Heidelberg
Rathke, F, Schmidt, S and Schnörr, C (2011). Order Preserving and Shape Prior Constrained Intra-Retinal Layer Segmentation in Optical Coherence Tomography. MICCAI 2011, Proceedings. Springer. 6893 370-377
Rathke, F and Schnörr, C (2015). A Computational Approach to Log-Concave Density Estimation. An. St. Univ. Ovidius Constanta. 23 151-166
Rath, R (1992). Amplitudenmessung Von Wasseroberflächenwellen Mittels Digitaler Bildanalyse. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg
Rapp, H, Frank, M, Hamprecht, F A and Jähne, B (2008). A theoretical and experimental investigation of the systematic errors and statistical uncertainties of time-of-flight cameras. Int. J. Intelligent Systems Technologies and Applications. 5 402--413
Rapp, H, Frank, M, Hamprecht, F A and Jähne, B (2008). A Theoretical and Experimental Investigation of the Systematic Errors and Statistical Uncertainties of Time-of-Flight Cameras. Int. J. Intelligent Systems Technologies and Applications. 5 402-413PDF icon Technical Report (798.23 KB)
Rapp, H (2007). Experimental And Theoretical Investigation Of Correlating Tof-Camera Systems. IWR, Fakultät für Physik und Astronomie, Universität Heidelberg. http://www.ub.uni-heidelberg.de/archiv/7666
Rapp, H, Frank, M, Hamprecht, F A and Jähne, B (2007). A theoretical and experimental investigation of the systematic errors and statistical uncertainties of time-of-flight cameras. Proc.\ Dyn3D Workshop, Heidelberg, Sept. 11, 2007. ZESS, Univ.\ Siegen
Raisch, F, Scharr, H, Kirchgeßner, N, Jähne, B, Fink, R H A and Uttenweiler, D (2002). Velocity and feature estimation of actin filaments using active contours in noisy fluorescence image sequences. Proc. 2nd IASTED Int. Conf. Visualization, Imaging and Image Processing. 645--650
Raisch, F (2004). Aktive Konturen zur Objektsegmentierung in stark verrauschten Bildsequenzen und zur Segmentierung von Bonddrähten in der industriellen Bildverarbeitung. Univ.\ Mannheim. http://d-nb.info/972877436
Rahaman, N, Arpit, D, Baratin, A, Draxler, F, Lin, M, Hamprecht, F A, Bengio, Y and Courville, A (2018). On the spectral bias of deep neural networks. arXiv preprint arXiv:1806.08734
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Prokop, M (2000). Bestimmung Physiologischer Parameter Von Pflanzen Mittels Digitaler Bildverarbeitung. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg
Preusser, T, Droske, M, Garbe, C S, Rumpf, M and Telea, A (2007). A phase field method for joint denoising, edge detection, and motion estimation in image sequence processing.. SIAM Journal of Applied Mathematics. 68 599-618
Prange, T (2016). Automatic Segmentation Of Neurons In Electron Microscopy Data With Membrane Defects. University of Heidelberg
Popp, C (2006). Untersuchung von Austauschprozessen an der Wasseroberfläche aus Infrarot-Bildsequenzen mittels frequenzmodulierter Wärmeeinstrahlung. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg. http://www.ub.uni-heidelberg.de/archiv/6489
Platt, T (2011). Weiterentwicklung Einer Hochauflösenden Lif-Methode Zur Messung Von Sauerstoffkonzentrationsprofilen In Der Wasserseitigen Grenzschicht. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg
Pfannmöller, M, Flügge, H, Benner, G, Wacker, I, Sommer, C, Hanselmann, M, Schmale, S, Schmidt, H, Hamprecht, F A, Rabe, T, Kowalsky, W and Schröder, R (2011). Visualizing a homogeneous blend in bulk heterojunction polymer solar cells by analytical electron microscopy. Nano Letters. 11 3099-3107
Petra, S, Popa, C and Schnörr, C (2008). Enhancing Sparsity by Constraining Strategies: Constrained SIRT versus Spectral Projected Gradient Methods. Proc.~7th Workshop on Modelling of Environmental and Life Sciences Problems (WMM~08). Ed Acad Romane, Bucuresti
Petra, S, Schröder, A, Wieneke, B and Schnörr, C (2008). On Sparsity Maximization in Tomographic Particle Image Reconstruction. Pattern Recognition -- 30th DAGM Symposium. Springer Verlag. 5096 294--303PDF icon Technical Report (1014.71 KB)
Petra, S, Schnörr, C, Becker, F and Lenzen, F (2013). B-SMART: Bregman-Based First-Order Algorithms for Non-Negative Compressed Sensing Problems. Proceedings of the 4th International Conference on Scale Space and Variational Methods in Computer Vision SSVM. 110-124
Petra, S, Schnörr, C, Schröder, A and Wieneke, B (2007). Tomographic Image Reconstruction in Experimental Fluid Dynamics: Synopsis and Problems. Proc.~6th Workshop on Modelling of Environmental and Life Sciences Problems (WMM~07). Ed Acad Romane, Bucuresti
Petra, S, Popa, C and Schnörr, C (2008). Extended And Constrained Cimmino-Type Algorithms With Applications In Tomographic Image Reconstruction. IWR, University of Heidelberg. http://www.ub.uni-heidelberg.de/archiv/8798/PDF icon Technical Report (2.13 MB)
Petra, S, Schnörr, C and Schröder, A (2012). Critical Parameter Values and Reconstruction Properties of Discrete Tomography: Application to Experimental Fluid Dynamics. http://arxiv.org/abs/1209.4316
Petra, S, Schnörr, C, Becker, F and Lenzen, F (2013). B-SMART: Bregman-Based First-Order Algorithms for Non-Negative Compressed Sensing Problems. Proceedings of the 4th International Conference on Scale Space and Variational Methods in Computer Vision (SSVM) 2013. Springer. 7893 110-124PDF icon Technical Report (1.15 MB)
Petra, S, Popa, C and Schnörr, C (2009). Accelerating Constrained Sirt With Applications In Tomographic Particle Image Reconstruction. IWR, University of Heidelberg. http://www.ub.uni-heidelberg.de/archiv/9477PDF icon Technical Report (3.33 MB)

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