Publications

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Pandey, N (2019). Weakly Supervised Semantic Segmentation. Heidelberg University
Pape, C (2016). Automatic Segmentation Of Neurites From Anisotropic Em-Imaging. University of Heidelberg
Pape, C, Beier, T, Li, P, Jain, V, Brock, D D and Kreshuk, A (2017). Solving Large Multicut Problems for Connectomics via Domain Decomposition. Bioimage Computing Workshop. ICCV. 1-10
Papst, M (2019). Development Of A Method For Quantitative Imaging Of Air-Water Gas Exchange. Institut für Umweltphysik, Universität Heidelberg, Germany
(2005). Variational, Geometric and Level Sets in Computer Vision (VLSM'05). lncs. Springer, Beijing, China. 3752
Pavlov, P (2008). Analysis of Motion in Scale Space. IWR, Fakultät für Mathematik und Informatik, Univ.\ Heidelberg. http://www.ub.uni-heidelberg.de/archiv/9378
Peckar, W, Schnörr, C, Rohr, K, Stiehl, H –S and Spetzger, U (1998). Linear and Incremental Estimation of Elastic Deformations in Medical Registration Using Prescribed Displacements. Machine Graphics & Vision. 7 807–829
Peckar, W, Schnörr, C, Rohr, K and Stiehl, H –S (1999). Parameter-Free Elastic Deformation Approach for 2D and 3D Registration Using Prescribed Displacements. J. Math. Imaging and Vision. 10 143–162
Peckar, W, Schnörr, C, Rohr, K and Stiehl, H S (1997). Two-Step Parameter-Free Elastic Image Registration with Prescribed Point Displacements. Proc. 9th Int. Conf. on Image Analysis and Processing (ICIAP'97). Florence, Italy
Peckar, W, Schnörr, C, Rohr, K and Stiehl, H S (1998). Non-Rigid Image Registration Using a Parameter-Free Elastic Model. 9th British Machine Vision Conference (BMVC`98). Southampton/UK. 134–143
Peter, S, Diego, F, Hamprecht, F A and Nadler, B (2017). Cost-efficient Gradient Boosting. NIPS, poster
Peter, S, Kirschbaum, E, Both, M, Campbell, L A, Harvey, B K, Heins, C, Durstewitz, D, Diego, F and Hamprecht, F A (2017). Sparse convolutional coding for neuronal assembly detection. NIPS, poster
Peter, S (2019). Machine learning under test-time budget constraints. Heidelberg University
Peter, S (2015). Spatio-Temporal Motif Deconvolution For Calcium Image Analysis. University of Heidelberg
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/
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, Constanta, Romania
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). Bucharest, Romania
Petra, S and Schnörr, C (2009). Tomopiv Meets Compressed Sensing. IWR, University of Heidelberg. http://www.ub.uni-heidelberg.de/archiv/9760
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, Constanta, Romania
Petra, S and Schnörr, C (2009). TomoPIV meets Compressed Sensing. Pure Math. Appl. 20 49 – 76. http://www.mat.unisi.it/newsito/puma/public_html/contents.php
Petra, S, Schröder, A and Schnörr, C (2009). 3D Tomography from Few Projections in Experimental Fluid Mechanics. Imaging Measurement Methods for Flow Analysis. Springer. 106 63-72PDF icon Technical Report (411.51 KB)
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 and Schröder, A (2013). Critical Parameter Values and Reconstruction Propertiesof Discrete Tomography: Application to Experimental FluidDynamics. Fundamenta Informaticae. 125 285--312PDF icon Technical Report (1.42 MB)
Petra, S and Schnörr, C (2009). TomoPIV meets Compressed Sensing. Pure Math.~Appl. 20 49 -- 76. http://www.mat.unisi.it/newsito/puma/public_html/contents.phpPDF icon Technical Report (409.1 KB)
Petra, S and Schnörr, C (2014). Average Case Recovery Analysis of Tomographic Compressive Sensing. Linear Algebra and its Applications. 441 168-198PDF icon Technical Report (1.85 MB)
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 and Schnörr, C (2009). Tomopiv Meets Compressed Sensing. IWR, University of Heidelberg. http://www.ub.uni-heidelberg.de/archiv/9760PDF icon Technical Report (646.75 KB)
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, 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)
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, Schröder, A, Wieneke, B and Schnörr, C (2008). On Sparsity Maximization in Tomographic Particle Image Reconstruction. Pattern Recognition – 30th DAGM Symposium. Springer Verlag. 5096 294–303
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
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
Pinggera, P, Ramos, S, Gehrig, S, Franke, U, Rother, C and Mester, R (2016). Lost and found: Detecting small road hazards for self-driving vehicles. IEEE International Conference on Intelligent Robots and Systems. 2016-Novem 1099–1106. http://www.6d-vision.com/lostandfounddataset
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

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