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Publications

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Rother, C, Kumar, S, Kolmogorov, V and Blake, A (2005). Digital tapestry [automatic image synthesis]. Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on. 1 589–596. http://research.microsoft.com/ http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=1467321%5Cnhttp://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1467321
Kandemir, M, Feuchtinger, A, Walch, A and Hamprecht, F A (2014). Digital Pathology: Multiple instance learning can detect Barrett'scancer. ISBI. Proceedings. 1348-1351PDF icon Technical Report (2.86 MB)
Jähne, (1997). Digital Image Processing - Concepts, Algorithms, And Scientific Applications, 4th ed. Springer. http://d-nb.info/950918016
Jähne, (1995). Digital Image Processing --- Concepts, Algorithms, And Scientific Applications, 3rd ed. Springer. http://d-nb.info/945151500
Jähne, (1993). Digital Image Processing --- Concepts, Algorithms, And Scientific Applications, 2nd ed. Springer. http://d-nb.info/931193567
Jähne, (1991). Digital Image Processing - Concepts, Algorithms, And Scientific Applications. Springer. http://d-nb.info/911090657
Jähne, (2005). Digital Image Processing, 6th ed. Springer
Jähne, (2002). Digital Image Processing, 5thth ed. Springer. http://d-nb.info/963597833
Bell, P and Ommer, B (2016). Digital Connoisseur? How Computer Vision Supports Art History. Connoisseurship nel XXI secolo. Approcci, Limiti, Prospettive, A. Aggujaro & S. Albl (ed.). Artemide, Rome
Vijayan, A, Tofanelli, R, Strauss, S, Cerrone, L, Wolny, A, Strohmeier, J, Kreshuk, A, Hamprecht, F A, Smith, R S and Schneitz, K (2021). A Digital 3D Reference Atlas Reveals Cellular Growth Patterns Shaping the Arabidopsis Ovule. eLife
Cremers, D, Schnörr, C and Weickert, J (2001). Diffusion–Snakes: Combining Statistical Shape Knowledge and Image Information in a Variational Framework. IEEE First Workshop on Variational and Level Set Methods in Computer Vision. IEEE Comp. Soc., Vancouver, Canada. 237–244
Cremers, D, Schnörr, C, Weickert, J and Schellewald, C (2000). Diffusion Snakes Using Statistical Shape Knowledge. Proc. Algebraic Frames for the Perception-Action Cycle. Springer, Kiel. 1888 164–174
Cremers, D, Tischhäuser, F, Weickert, J and Schnörr, C (2002). Diffusion Snakes: Introducing Statistical Shape Knowledge into the Mumford–Shah functional. Int. J. Computer Vision. 50 295–313
Spies, H, Haußecker, H, Jähne, B and Barron, J L (1999). Differential range flow estimation. Proceedings of the 21th DAGM Symposium on Pattern Recognition. 309--316
Steen, J A J, Steen, H, Georgi, A, Parker, K C, Springer, M, Kirchner, M, Hamprecht, F A and Kirschner, M W (2008). Different Phosphorylation States of the Anaphase Promoting Complex in Response to Anti-Mitotic Drugs: A Quantitative Proteomic Analysis. Proceedings of the National Academy of Sciences. 105 6069-6074PDF icon Technical Report (173.02 KB)
Libner, P (1987). Die Konstantflußmethode: Ein neuartiges, schnelles und lokales Meßverfahren zur Untersuchung von Austauschvorgängen an der Luft-Wasser Phasengrenze. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg. http://d-nb.info/881465941
Weilbach, C (2018). Dictionary Learning With Bayesian Gans For Few-Shot Classification. Heidelberg University
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
Bauer, P Salomon (2013). Development Of An Imaging Polarimeter For Water Wave Slope Measurements. Institut für Umwelphysik, Univeristät Heidelberg, Germany. http://www.ub.uni-heidelberg.de/archiv/15899
Kiefhaber, D (2010). Development Of A Reflective Stereo Slope Gauge For The Measurement Of Ocean Surface Wave Slope Statistics. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg. http://www.ub.uni-heidelberg.de/archiv/12673/
Papst, M (2019). Development Of A Method For Quantitative Imaging Of Air-Water Gas Exchange. Institut für Umweltphysik, Universität Heidelberg, Germany
Schwarz, T S (2005). Development Of A Depth Resolving Boundary Layer Visualiziation Für Gas Exchange At Free Water Surfaces. University of Heidelberg
Hamprecht, F A, Cohen, A J, Tozer, D J and Handy, N C (1998). Development and assessment of new exchange-correlation functionals. Journal of Chemical Physics. 109 6264-6271
Lou, X, Kirchner, M, Renard, B Y, Köthe, U, Graf, C, Lee, C, Steen, J A J, Steen, H, Mayer, M P and Hamprecht, F A (2010). Deuteration Distribution Estimation with Improved Sequence Coverage for HX/MS Experiments. Bioinformatics. 26(12) 1535-1541PDF icon Technical Report (518.01 KB)
Fornland, P and Schnörr, C (1997). Determining the Dominant Plane from Uncalibrated Stereo Vision by a Robust and Convergent Iterative Approach without Correspondence. Proc. Int. Conf. Comp. Vision and Patt. Recog. (CVPR'97). San Juan, Puerto Rico
Schnörr, (1991). Determining Optical Flow for Irregular Domains by Minimizing Quadratic Functionals of a Certain Class. ijcv. 6 25–38
Görlitz, L, Hamprecht, F A and Staudacher, M (2005). Detektion von Partikeln in Intensitätsbildern mit Hilfe eines morphologischen Skalenraumes. Robert-Bosch GmbH, University of Heidelberg
Sprengel, R, Schnörr, C and Neumann, B (1994). Detection of Visual Data Transitions in Nonlinear Parameter Space. Mustererkennung 1994. Technische Universität Wien. 5 315–323
Eyjolfsdottir, E, Branson, S, Burgos-Artizzu, X P, Hoopfer, E D, Schor, J, Anderson, D J and Perona, P (2014). Detection of social actions in fruit flies. Lecture Notes in Computer Science. Springer International Publishing, Cham. 8690 772–787. http://link.springer.com/10.1007/978-3-319-10605-2 http://www.ncbi.nlm.nih.gov/pubmed/31629782
Köhler, H - J, Haußecker, H and Jähne, B (1996). Detection of particle movements at soil interfaces due to changing hydraulic load conditions, localised by a digital image processing technique. Proc. Geofilters 1996, Montreal. Ecole Polytechnique Montreal
Menze, B H, Ur, J A and Sherratt, A G (2006). Detection of ancient settlement mounds - Archaeological survey based on the SRTM terrain model. Photgrammetric Engineering & Remote Sensing. 3 321-327PDF icon Technical Report (643.89 KB)
Ramos, S, Gehrig, S, Pinggera, P, Franke, U and Rother, C (2017). Detecting unexpected obstacles for self-driving cars: Fusing deep learning and geometric modeling. IEEE Intelligent Vehicles Symposium, Proceedings. 1025–1032. http://arxiv.org/abs/1612.06573
Decker, C and Hamprecht, F A (2014). Detecting individual body parts improves mouse behavior classification. Workshop on visual observation and analysis of Vertebrate And Insect Behavior (VAIB), 22nd International Conference on Pattern Recognition (ICPR). ProceedingsPDF icon Technical Report (1.48 MB)
Schlecht, J, Carque, B and Ommer, B (2011). Detecting Gestures in Medieval Images. Proceedings of the International Conference on Image Processing. IEEE. 1309--1312PDF icon Technical Report (1.61 MB)
Bruhn, A, Jakob, T, Fischer, M, Kohlberger, T, Weickert, J, Brüning, U and Schnörr, C (2002). Designing 3–D Nonlinear Diffusion Filters for High Performance Cluster Computing. Pattern Recognition, Proc. 24th DAGM Symposium. Springer, Zürich, Switzerland. 2449 290–297

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