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L. Schott, “Learned Watershed Algorithm: End-to-End Learning of Seeded Segmentation”, Heidelberg University, 2017.
M. Scholze, “Analyse der visuellen Stratigraphie alpiner Eisbohrkerne mittels digitaler Bildverarbeitung”, Fakultät für Physik und Astronomie Universität Heidelberg, 1998.
J. Scholz, Wiersbinski, T., Ruhnau, P., Kondermann, D., Garbe, C. S., Hain, R., and Beushausen, V., “Double-pulse planar-LIF investigations using fluorescence motion analysis for mixture formation investigation”, Exp. Fluids, vol. 45, p. 583--593, 2008.
J. Scholz, Wiersbinski, T., Ruhnau, P., Kondermann, D., Garbe, C. S., Hain, R., and Beushausen, V., “Double-pulse planar-LIF investigations using fluorescence motion analysis for mixture formation investigation”, in 7th International Symposium on Particle Image Velocimetry Rome, 11. - 14.Sept., 2007.
T. Scholz, “Ein Depth from Focus-Verfahren zur On Line-Bestimmung der Zell-kon-zentration bei Fermentationsprozessen”. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 1995.
T. Scholz, “Bildfolgenanalyse von Wasseroberflächenwellen auf dem Transputer”, IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 1991.
T. Scholz, Jähne, B., Suhr, H., Wehnert, G., Geissler, P., and Schneider, K., “In-situ determination of cell concentration in bioreactors with a new depth-from-focus technique”, in Proc.\ Optical 3-D Measurement Techniques IV, Zurich, Sept. 29 - Oct. 2, 1997, 1996, p. 392--399.
T. Scholz, Jähne, B., Suhr, H., Wehnert, G., Geissler, P., and Schneider, K., “In situ determination of cell concentration in bioreactors with a new depth from focus technique”, in Computer Analysis of Images and Patterns, 1995, vol. 970, p. 392--399.
T. Scholz, Jähne, B., Suhr, H., Wehnert, G., Geißler, P., and Schneider, K., “A new depth from focus technique for in situ determination of cell concentration in bioreactors”, in Proc. 16. DAGM-Symposium Mustererkennung, 1994, p. 145--150.
M. C. Scholes, Matrai, P. A., Andreae, M. O., Smith, K. A., Manning, M. R., Artaxo, P., Barrie, L. A., Bates, T. S., Butler, J. H., Ciccioli, P., Cieslik, S. A., Delmas, R. J., and Dentener, F. J., “Biosphere-Atmosphere Interactions”, Atmospheric Chemistry in a Changing World, An Integration and Synthesis of a Decade of Tropospheric Chemistry Research. Springer, p. 19--71, 2003.
M. Schoder, “Messung der Transfergeschwindigkeit des Gasaustausches durch Blasenoberflächen”, Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 1984.
C. Schnörr, “Signal and Image Approximation with Level-Set Constraints”, Computing, vol. 81, pp. 137-160, 2007.PDF icon Technical Report (506.8 KB)
C. Schnörr, “Assignment Flows”, Handbook of Variational Methods for Nonlinear Geometric Data. Springer, p. 235—260, 2020.
C. Schnörr, “Assignment Flows”, Variational Methods for Nonlinear Geometric Data and Applications. Springer, 2019.
C. Schnörr, “Zur Schätzung von Geschwindigkeitsvektorfeldern in Bildfolgen mit einer richtungsabhängigen Glattheitsforderung”, in Mustererkennung 1989, 11. DAGM-Symposium, Hamburg, 1989, vol. 219, pp. 294–301.
C. Schnörr, “Repräsentation von Bilddaten mit einem konvexen Variationsansatz”, in Mustererkennung 1996, Berlin, Heidelberg, 1996, pp. 21–28.
C. Schnörr, “Variational Adaptive Smoothing and Segmentation”, in Computer Vision and Applications: A Guide for Students and Practitioners, San Diego, 2000, pp. 459–482.
C. Schnörr, “Variational Methods for Adaptive Image Smoothing and Segmentation”, in Handbook on Computer Vision and Applications: Signal Processing and Pattern Recognition, San Diego, 1999, vol. 2, pp. 451–484.
C. Schnörr, “Bewegungssegmentation von Bildfolgen durch die Minimierung konvexer nicht-quadratischer Funktionale”, in Mustererkennung 1994, 1994, vol. 5, pp. 178–185.
C. Schnörr, “Signal and Image Approximation with Level-Set Constraints”, Computing, vol. 81, pp. 137-160, 2007.
C. Schnörr, “Statistische Mustererkennung”. 2001.
C. Schnörr, “Variational approaches to Image Segmentation and Feature Extraction”. University of Hamburg, Comp. Sci. Dept., Hamburg, Germany, 1998.
C. Schnörr, “A Study of a Convex Variational Diffusion Approach for Image Segmentation and Feature Extraction”, J. of Math. Imag. and Vision, vol. 8, pp. 271–292, 1998.
C. Schnörr, “Representation of Images by a Convex Variational Diffusion Approach”, FB Informatik, Universität Hamburg, FBI-HH-M-256/96, 1996.
C. Schnörr, “Segmentation of Visual Motion by Minimizing Convex Non-Quadratic Functionals”, in 12th Int. Conf. on Pattern Recognition, Jerusalem, Israel, 1994.
C. Schnörr, “Unique Reconstruction of Piecewise Smooth Images by Minimizing Strictly Convex Non-Quadratic Functionals”, vol. 4, pp. 189–198, 1994.
C. Schnörr, “On Functionals with Greyvalue-Controlled Smoothness Terms for Determining Optical Flow”, pami, vol. 15, pp. 1074–1079, 1993.
C. Schnörr, “Computation of Discontinuous Optical Flow by Domain Decomposition and Shape Optimization”, ijcv, vol. 8, pp. 153–165, 1992.
C. Schnörr, “Funktionalanalytische Methoden zur Bestimmung von Bewegungsinformation aus TV-Bildfolgen”. Fakultät für Informatik, Universität Karlsruhe (TH), 1991.
C. Schnörr, “Determining Optical Flow for Irregular Domains by Minimizing Quadratic Functionals of a Certain Class”, ijcv, vol. 6, pp. 25–38, 1991.
C. Schnörr, “Computation of Discontinuous Optical Flow by Domain Decomposition and Shape Optimization”, in Proc. British Machine Vision Conference, Oxford/UK, 1990, pp. 109–114.
C. Schnörr and Neumann, B., “Ein Ansatz zur effizienten und eindeutigen Rekonstruktion stückweise glatter Funktionen”, in Mustererkennung 1992, 14. DAGM-Symposium, Dresden, 1992, pp. 411–416.
C. Schnörr, Niemann, H., and Kopecz, J., “Architekturkonzepte zur Bildauswertung”, in Grundlagen und Anwendungen der Künstlichen Intelligenz, 17. Fachtagung für Künstliche Intelligenz, Berlin, 1993, pp. 268–274.
C. Schnörr and Peckar, W., “Motion-Based Identification of Deformable Templates”, in Proc. 6th Int. Conf. on Computer Analysis of Images and Patterns (CAIP '95), Prague, Czech Republic, 1995, vol. 970, pp. 122-129.
C. Schnörr, Schüle, T., and Weber, S., “Variational Reconstruction with DC-Programming”, Advances in Discrete Tomography and Its Applications. Birkhäuser, Boston, 2007.

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