Publications

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Schmitzer, B and Schnörr, C (2013). Modelling convex shape priors and matching based on the Gromov-Wasserstein distance. Journal of Mathematical Imaging and Vision. 46 143-159
Schmund, D (1995). Voruntersuchung Der Einsatzmöglichkeiten Digitaler Bildverarbeitung Zur Analyse Von Transportvorgängen Und Wachstumsprozessen In Pflanzen. University of Heidelberg
Schmund, D (1999). Development of an Optical Flow Based System for the Precise Measurement of Plant Growth. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg
Schmund, D, Stitt, M, Jähne, B and Schurr, U (1998). Quantitative analysis of the local rates of growth of dicot leaves at a high temporal and spatial resolution, using image sequence analysis. Plant Journal. 16 505--514
Schmund, D, Schurr, U, Jähne, B, Haußecker, H and Geißler, P (1999). Plant-leaf growth studied by image sequence analysis. Handbook of Computer Vision and Applications. Academic Press. 3: Systems and Applications 719-735
Schmund, D, Schurr, U and Jähne, B (2000). Optical leaf growth analysis. Computer Vision and Applications - A Guide for Students and Practitioners. Academic Press. 640-641
Schmund, D, Münsterer, T, Lauer, H, Jähne, B and Jähne, B (1995). The circular wind wave facilities at the University of Heidelberg. Air-Water Gas Transfer - Selected papers from the Third International Symposium on Air-Water Gas Transfer. AEON. 505--516
Schnieders, J (2011). Investigation Of Momentum Transfer Across The Air-Sea Interface By Means Of Active And Passive Thermography. Interdisciplinary Center for Scientific Computing (IWR), University of Heidelberg
Schnörr, (1998). A Study of a Convex Variational Diffusion Approach for Image Segmentation and Feature Extraction. J. of Math. Imag. and Vision. 8 271–292
Schnörr, C and Neumann, B (1992). Ein Ansatz zur effizienten und eindeutigen Rekonstruktion stückweise glatter Funktionen. Mustererkennung 1992, 14. DAGM-Symposium. Springer-Verlag, Dresden. 411–416
Schnörr, (1999). Variational Methods for Adaptive Image Smoothing and Segmentation. Handbook on Computer Vision and Applications: Signal Processing and Pattern Recognition. Academic Press, San Diego. 2 451–484
Schnörr, (1993). On Functionals with Greyvalue-Controlled Smoothness Terms for Determining Optical Flow. pami. 15 1074–1079
Schnörr, C and Sprengel, R (1994). A Nonlinear Regularization Approach to Early Vision. Biol. Cybernetics. 72 141–149
Schnörr, (2019). Assignment Flows. Variational Methods for Nonlinear Geometric Data and Applications. Springer
Schnörr, (1998). Variational approaches to Image Segmentation and Feature Extraction. University of Hamburg, Comp. Sci. Dept., Hamburg, Germany
Schnörr, (1990). Computation of Discontinuous Optical Flow by Domain Decomposition and Shape Optimization. Proc. British Machine Vision Conference. Oxford/UK. 109–114
Schnörr, (1996). Convex Variational Segmentation of Multi-Channel Images. Proc. 12th Int. Conf. on Analysis and Optimization of Systems: Images, Wavelets and PDE's. Springer-Verlag, Paris. 219
Schnörr, (2000). Variational Adaptive Smoothing and Segmentation. Computer Vision and Applications: A Guide for Students and Practitioners. Academic Press, San Diego. 459–482
Schnörr, (1994). Unique Reconstruction of Piecewise Smooth Images by Minimizing Strictly Convex Non-Quadratic Functionals. 4 189–198
Schnörr, (2020). Assignment Flows. Handbook of Variational Methods for Nonlinear Geometric Data. Springer. 235—260. https://www.springer.com/gp/book/9783030313500
Schnörr, C, Schüle, T and Weber, S (2007). Variational Reconstruction with DC-Programming. Advances in Discrete Tomography and Its Applications. Birkhäuser, Boston
Schnörr, (2007). Signal and Image Approximation with Level-Set Constraints. Computing. 81 137-160PDF icon Technical Report (506.8 KB)
Schnörr, (2001). Statistische Mustererkennung
Schnörr, (1991). Determining Optical Flow for Irregular Domains by Minimizing Quadratic Functionals of a Certain Class. ijcv. 6 25–38
Schnörr, C and Weickert, J (2000). Variational Image Motion Computation: Theoretical Framework, Problems and Perspectives. Mustererkennung 2000. Springer, Kiel, Germany
Schnörr, (1996). Repräsentation von Bilddaten mit einem konvexen Variationsansatz. Mustererkennung 1996. Springer-Verlag, Berlin, Heidelberg. 21–28
Schnörr, (1994). Segmentation of Visual Motion by Minimizing Convex Non-Quadratic Functionals. 12th Int. Conf. on Pattern Recognition. Jerusalem, Israel
Schnörr, C and Peckar, W (1995). Motion-Based Identification of Deformable Templates. Proc. 6th Int. Conf. on Computer Analysis of Images and Patterns (CAIP '95). Springer Verlag, Prague, Czech Republic. 970 122-129
(2000). Künstliche Intelligenz: Special Issue on Medical Computer Vision. 3
Schnörr, (2007). Signal and Image Approximation with Level-Set Constraints. Computing. 81 137-160
Schnörr, (1991). Funktionalanalytische Methoden zur Bestimmung von Bewegungsinformation aus TV-Bildfolgen. Fakultät für Informatik, Universität Karlsruhe (TH)
Schnörr, C, Stiehl, H - S and Grigat, R - R (1996). On Globally Asymptotically Stable Continuous-Time CNNs for Adaptive Smoothing of Multidimensional Signals. Proc. 4th IEEE Int. Workshop on Cellular Neural Networks and their Applications. Seville, Spain
Schnörr, (1989). Zur Schätzung von Geschwindigkeitsvektorfeldern in Bildfolgen mit einer richtungsabhängigen Glattheitsforderung. Mustererkennung 1989, 11. DAGM-Symposium. Springer-Verlag, Hamburg. 219 294–301
Schnörr, (1996). Representation Of Images By A Convex Variational Diffusion Approach. FB Informatik, Universität Hamburg
Schnörr, C, Niemann, H and Kopecz, J (1993). Architekturkonzepte zur Bildauswertung. Grundlagen und Anwendungen der Künstlichen Intelligenz, 17. Fachtagung für Künstliche Intelligenz. Springer-Verlag, Berlin. 268–274

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