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Wierzimok, D (1990). Messung turbulenter Strömungen unterhalb der windwellenbewegten Wasseroberfläche mittels digitaler Bildverarbeitung. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg. http://d-nb.info/910573255

Wierzimok, D and Hering, F (1993). Quantitative imaging of transport in fluids with digital particle tracking velocimetry. Imaging in Transport Processes. Begell House Publishers. 297--308. http://www.dl.begellhouse.com/references/1bb331655c289a0a,36adf33e6f249361.html

Wierzimok, D, Jähne, B and Dengler, J (1987). Bildfolgenanalyse dreidimensionaler turbulenter Strömungen. Proc. 9. DAGM-Symposium zur Mustererkennung 1987. Springer. 149 288

Wierzimok, D and Jähne, B (1990). Automatic particle tracking beneath a wind-stressed wavy water surface with image processing. Proc.\ 5th Int. Symposium Flow Visualization, Praque 1989. 943--956

Wierzimok, D and Jähne, B (1991). Measurement of wave-induced turbulent flow structure using digital image sequence analysis. Air-Water Mass Transfer, selected papers from the 2nd International Symposium on Gas Transfer at Water Surfaces, September 11--14, 1990, Minneapolis, Minnesota. ASCE. 200--209

Wierzimok, D, Hering, F and Brunswig, F (1992). Tracking in Strömungsbildfolgen. Proc. 14. DAGM-Symposium Mustererkennung. Springer

Winter, R (2011). Fluorescent Tracers for air-sided Concentration Profile Measurements at the Air-Water Interface. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ. Heidelberg. Dissertation. http://www.ub.uni-heidelberg.de/archiv/12105

Withopf, D and Jähne, B (2006). Learning algorithm for real-time vehicle tracking. Proc. IEEE Intelligent Transportation Systems Conference ITSC '06. 516--521

Withopf, D and Jähne, B (2007). Improved training algorithm for tree-like classifiers and its application to vehicle detection. Proc. IEEE Intelligent Transportation Systems Conference (ITSC). 642--647

Withopf, D (2007). Reliable Real-Time Vehicle Detection and Tracking. IWR, Fakultät für Mathematik und Informatik, Univ.\ Heidelberg. http://d-nb.info/98745398X

Wolf, S, Hamprecht, F A and Funke, J (2020). Instance Separation Emerges from Inpainting. arXiv preprint arXiv:2003.00891

Wolf, S, Hamprecht, F A and Funke, J (2020). Inpainting Networks Learn to Separate Cells in Microscopy Images. BMCV

Technical Report (357.23 KB)

Wolf, S, Li, Y, Pape, C, Bailoni, A, Kreshuk, A and Hamprecht, F A (2020). The Semantic Mutex Watershed for Efficient Bottom-Up Semantic Instance Segmentation. ECCV. Proceedings. 208-224

Wolf, S (2020). Machine Learning for Instance Segmentation. Heidelberg University

Wolf, S, Bailoni, A, Pape, C, Rahaman, N, Kreshuk, A, Köthe, U and Hamprecht, F A (2020). The Mutex Watershed and its Objective: Efficient, Parameter-Free Graph Partitioning. IEEE Transactions on Pattern Analysis and Machine Intelligence. 43 3724-3738

Technical Report (2.58 MB)

Wolf, C (1994). Surface Properties Of Breaking Water Waves. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg

Wolf, G (1981). Aufbau Einer Pilotanlage Zur Gaschromatographischen Tritiumanreicherung. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg

Wolf, S (2016). Cell Tracking With Graphical Model Using Higher Order Features On Track Segments. University of Heidelberg

Wolf, S, Schott, L, Köthe, U and Hamprecht, F A (2017). Learned Watershed: End-to-End Learning of Seeded Segmentation. ICCV. 2030-2038

Technical Report (3.76 MB)

Wolf, S, Pape, C, Bailoni, A, Rahaman, N, Kreshuk, A, Köthe, U and Hamprecht, F A (2018). The Mutex Watershed: Efficient, Parameter-Free Image Partitioning. ECCV. Proceedings. Springer. 571-587

Wolf, S, Pape, C, Bailoni, A, Rahaman, N, Kreshuk, A, Köthe, U and Hamprecht, F A (2018). The Mutex Watershed: Efficient, Parameter-Free Image Partitioning. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 11208 LNCS 571–587. http://arxiv.org/abs/1904.12654

Wolny, A, Cerrone, L, Vijayan, A, Tofanelli, R, Vilches-Barro, A, Louveaux, M, Wenzel, C, Strauss, S, Wilson-Sanchez, D, Lymbouridou, R, Steigleder, S S, Pape, C, Bailoni, A, Duran-Nebreda, S, Bassel, G W, Lohmann, J U, Tsiantis, M, Hamprecht, F A, Schneitz, K, Maizel, A and Kreshuk, A (2020). Accurate and Versatile 3D Segmentation of Plant Tissues at Cellular Resolution. eLife. 9

Woodford, O J (2009). A Global Perspective on MAP Inference for Low-Level Vision Supplementary material to ICCV submission \# 1536. Optimization

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

Wulf, M, Stiehl, H S and Schnörr, C (1999). A model of spatiotemporal receptive fields in the primate retina. Proc. 1st Göttingen Conf. German Neurosci. Soc.. II

Wulf, M, Stiehl, H S and Schnörr, C (1999). Modeling spatiotemporal receptive fields in the primate retina. Proc. Cognitive Neurosci. Conf. Hanse–Wissenschaftskolleg, Bremen, Germany

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