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S. T. Radev, Mertens, U. K., Voss, A., Ardizzone, L., and Köthe, U., “BayesFlow: Learning complex stochastic models with invertible neural networks”, 2020.PDF icon PDF (5.36 MB)
N. Rahaman, Arpit, D., Baratin, A., Draxler, F., Lin, M., Hamprecht, F. A., Bengio, Y., and Courville, A., “On the spectral bias of deep neural networks”, arXiv preprint arXiv:1806.08734, 2018.
F. Raisch, “Aktive Konturen zur Objektsegmentierung in stark verrauschten Bildsequenzen und zur Segmentierung von Bonddrähten in der industriellen Bildverarbeitung”. Univ.\ Mannheim, 2004.
F. Raisch, Scharr, H., Kirchgeßner, N., Jähne, B., Fink, R. H. A., and Uttenweiler, D., “Velocity and feature estimation of actin filaments using active contours in noisy fluorescence image sequences”, in Proc. 2nd IASTED Int. Conf. Visualization, Imaging and Image Processing, 2002, p. 645--650.
S. Ramos, Gehrig, S., Pinggera, P., Franke, U., and Rother, C., “Detecting unexpected obstacles for self-driving cars: Fusing deep learning and geometric modeling”, in IEEE Intelligent Vehicles Symposium, Proceedings, 2017, pp. 1025–1032.
H. Rapp, “Experimental and Theoretical Investigation of Correlating TOF-Camera Systems”, IWR, Fakultät für Physik und Astronomie, Universität Heidelberg, 2007.
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.
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”, in Proc.\ Dyn3D Workshop, Heidelberg, Sept. 11, 2007, 2007.
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)
R. Rath, “Amplitudenmessung von Wasseroberflächenwellen mittels digitaler Bildanalyse”, Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 1992.
F. Rathke, Schmidt, S., and Schnörr, C., “Order Preserving and Shape Prior Constrained Intra-Retinal Layer Segmentation in Optical Coherence Tomography”, in MICCAI 2011, Proceedings, 2011, vol. 6893, pp. 370-377.
F. Rathke and Schnörr, C., “Fast Multivariate Log-Concave Density Estimation”, Comp. Statistics & Data Analysis, vol. 140, pp. 41–58, 2019.
F. Rathke and Schnörr, C., “Fast Multivariate Log-Concave Density Estimation”, preprint: arXiv, 2018.
F. Rathke, Desana, M., and Schnörr, C., “Locally Adaptive Probabilistic Models for Global Segmentation of Pathological OCT Scans”, in Proc. MICCAI, 2017.
F. Rathke, Schmidt, S., and Schnörr, C., “Probabilistic Intra-Retinal Layer Segmentation in 3-D OCT Images Using Global Shape Regularization”, Medical Image Analysis, vol. 18, pp. 781-794, 2014.
F. Rathke, Schmidt, S., and Schnörr, C., “Order Preserving and Shape Prior Constrained Intra-Retinal Layer Segmentation in Optical Coherence Tomography”, in MICCAI, 2011, vol. 6893, pp. 370–377.
F. Rathke, Schmidt, S., and Schnörr, C., “Probabilistic Intra-Retinal Layer Segmentation in 3-D OCT Images Using Global Shape Regularization”, Medical Image Analysis, vol. 18, pp. 781-794, 2014.PDF icon Technical Report (4.07 MB)
F. Rathke, Schmidt, S., and Schnörr, C., “Order Preserving and Shape Prior Constrained Intra-Retinal Layer Segmentation in Optical Coherence Tomography”, in MICCAI, 2011, vol. 6893, p. 370--377.PDF icon Technical Report (1.12 MB)
F. Rathke and Schnörr, C., “A Computational Approach to Log-Concave Density Estimation”, An. St. Univ. Ovidius Constanta, vol. 23, pp. 151-166, 2015.PDF icon Technical Report (1.07 MB)
F. Rathke, Hansen, K., Brefeld, U., and Müller, K. - R., “StructRank: A new approach for ligand-based virtual screening”, J. Chem. Inf. Model., vol. 51, pp. 83–92, 2010.
F. Rathke, Schmidt, S., and Schnörr, C., “Order preserving and shape prior constrained intra-retinal layer segmentation in optical coherence tomography”, Medical Image Computing and Computer-Assisted Intervention (MICCAI 2011), vol. 6893. Springer, pp. 370–377, 2011.
F. Rathke, Schmidt, S., and Schnörr, C., “Probabilistic Intra-Retinal Layer Segmentation in 3-D OCT Images Using Global Shape Regularization”, Med. Image Anal., vol. 18, pp. 781–794, 2014.
F. Rathke and Schnörr, C., “A Computational Approach to Log-Concave Density Estimation”, An. St. Univ. Ovidius Constanta, vol. 23, pp. 151-166, 2015.
F. Rathke, “Probabilistic Graphical Models for Medical Image Segmentation”. University Heidelberg, 2015.
F. Rathke, Desana, M., and Schnörr, C., “Locally Adaptive Probabilistic Models for Global Segmentation of Pathological OCT Scans”, MICCAI. Proceedings. pp. 177-184, 2017.PDF icon Technical Report (4.79 MB)
F. Rathke and Schnörr, C., “Fast Multivariate Log-Concave Density Estimation”, preprint: ArXiv, 2018.PDF icon Technical Report (3.54 MB)
F. Rathke and Schnörr, C., “Fast Multivariate Log-Concave Density Estimation”, Comp. Statistics & Data Analysis, vol. 140, pp. 41-58, 2019.
D. Rathore, “Semantic Segmentation Using Deep Learning”, University of Heidelberg, 2016.
A. Ravindran, “Novel Deep Learning-based Instance Segmentation Using Mutex Watershed for Microscopy Cell Images”, Heidelberg University, 2019.
H. Reinecke, “Methoden zur Bearbeitung und Merkmalsextrahierung von Zeitreihen aus technischen Anlagen”, IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 1997.
H. Reinecke, Fantana, N. L., Haußecker, H., and Jähne, B., “Rekonstruktion von Schreiberkurven”, in Mustererkennung 1997, 1997, p. 527--536.
S. Reinelt, “Bestimmung der Transfergeschwindigkeit mittels CFT mit Wärme als Tracer”, Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 1994.
J. Reinmuth, “Zwei-Farbstoff-Technik zur Tiefenrekonstruktion von Gaskonzentrationen in der wasserseitigen Grenzschicht”, Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 2000.
S. Reith, “Spatio-temporal slope measurement of short wind waves under the influence of surface films at the Heidelberg Aeolotron”, Institut für Umweltphysik, Universität Heidelberg, Germany, 2014.
R. Remme, “Instance Segmentation via Associative Pixel Embeddings”, Heidelberg University, 2019.

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