Export 180 results:
Author [ Title(Desc)] Type Year
Filters: Author is Schnörr, C.  [Clear All Filters]
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
Schüle, T, Weber, S and Schnörr, C (2005). Adaptive Reconstruction of Discrete-Valued Objects from few Projections. Electr. Notes in Discr. Math. 20 365-384
Schellewald, C, Roth, S and Schnörr, C (2001). Application Of Convex Optimization Techniques To The Relational Matching Of Object Views. Dept. Math. and Comp. Science, University of Mannheim, Germany
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
Schnörr, (2019). Assignment Flows. Variational Methods for Nonlinear Geometric Data and Applications. Springer
Schnörr, (2020). Assignment Flows. Handbook of Variational Methods for Nonlinear Geometric Data. Springer. 235—260.
Zern, A, Zeilmann, A and Schnörr, C (2020). Assignment Flows for Data Labeling on Graphs: Convergence and Stability. preprint: arXiv.
Aström, F, Petra, S, Schmitzer, B and Schnörr, C (2016). The Assignment Manifold: A Smooth Model for Image Labeling. Proc. 2nd Int. Workshop on Differential Geometry in Computer Vision and Machine Learning (DIFF-CVML'16; oral presentation; Grenander best paper award)
Bister, D, Rohr, K and Schnörr, C (1990). Automatische Bestimmung der Trajektorien von sich bewegenden Objekten aus einer Grauwertbildfolge. Mustererkennung 1990, 12. DAGM-Symposium. Springer-Verlag, Oberkochen-Aalen. 254 44–51
Heers, J, Schnörr, C and Stiehl, H S (1998). A class of parallel algorithms for nonlinear variational image segmentation. Proc. Noblesse Workshop on Non–Linear Model Based Image Analysis (NMBIA'98). Glasgow, Scotland
Neumann, J, Schnörr, C and Steidl, G (2005). Combined SVM-based Feature Selection and Classification. Machine Learning. 61 129-150
Dalitz, R, Petra, S and Schnörr, C (2017). Compressed Motion Sensing. Proc. SSVM. Springer. 10302
Schnörr, (1990). Computation of Discontinuous Optical Flow by Domain Decomposition and Shape Optimization. Proc. British Machine Vision Conference. Oxford/UK. 109–114
Schnörr, (1992). Computation of Discontinuous Optical Flow by Domain Decomposition and Shape Optimization. ijcv. 8 153–165
Wulf, M, Stiehl, H S and Schnörr, C (2000). On the computational rôle of the primate retina. Proc. 2nd ICSC Symposium on Neural Computation (NC 2000). Berlin, Germany
Lellmann, J and Schnörr, C (2010). Continuous Multiclass Labeling Approaches And Algorithms. Univ. of Heidelberg.
Lellmann, J and Schnörr, C (2011). Continuous Multiclass Labeling Approaches and Algorithms. CoRR. abs/1102.5448.
Savarino, F and Schnörr, C (2019). Continuous-Domain Assignment Flows. preprint: arXiv.
Keuchel, J, Schellewald, C, Cremers, D and Schnörr, C (2001). Convex Relaxations for Binary Image Partitioning and Perceptual Grouping. Mustererkennung 2001. Springer, Munich, Germany. 2191 353–360
Yuan, J, Schnörr, C, Kohlberger, T and Ruhnau, P (2004). Convex Set-Based Estimation of Image Flows. ICPR 2004 – 17th Int. Conf. on Pattern Recognition. IEEE, Cambridge, UK. 1 124-127
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
Petra, S, Schnörr, C and Schröder, A (2012). Critical Parameter Values and Reconstruction Properties of Discrete Tomography: Application to Experimental Fluid Dynamics.