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P

Rother, C, Carlsson, S and Tell, D (2002). Projective factorization of planes and cameras in multiple views. Proceedings - International Conference on Pattern Recognition. 16 737–740

Distributions, L (2014). Proof of Lemma 2 Proof of Lemma 3 Proof of Theorem 4 Proof of Lemma 10. Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics. 9–11

Schiegg, M, Heuer, B, Haubold, C, Wolf, S, Köthe, U and Hamprecht, F A (2015). Proof-reading Guidance in Cell Tracking by Sampling from Tracking-by-assignment Models. ISBI. Proceedings. 394-398

Technical Report (648.55 KB)

Bailoni, A, Pape, C, Wolf, S, Kreshuk, A and Hamprecht, F A (2020). Proposal-Free Volumetric Instance Segmentation from Latent Single-Instance Masks. GCPR. Springer. 12544 331-344

Heck, D (2004). Proximity Graphs For Nonlinear Dimension Reduction. University of Heidelberg

Pletscher, P, Nowozin, S, Kohli, P and Rother, C (2011). Putting MAP back on the map. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6835 LNCS 111–121

Pletscher, P, Nowozin, S, Kohli, P and Rother, C (2011). Putting MAP back on the map. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6835 LNCS 111–121

Q

Sieg, S, Stutz, B, Schmidt, T, Hamprecht, F A and Maier, W F (2006). A QCAR-approach to materials modelling. Journal of Molecular Modeling. 12 611-619

Technical Report (343.11 KB)

Blom, A H M, Brassel, J - O, von Brocke, M and Mittler, M (1999). Quality classification and process control of micro-spot laser welding. Proceedings of the Ninth International FAIM Conference - Flexible Automation and Intelligent Manufacturing, Tilburg. Begell House. 929--941

Lou, X, Fiaschi, L, Köthe, U and Hamprecht, F A (2012). Quality Classification of Microscopic Imagery with Weakly Supervised Learning. MICCAI-MLMI. Proceedings. 176-183

Technical Report (4.15 MB)

König, (2007). Quality Control In Mass Spectrometry. University of Heidelberg

Kassemeyer, S (2009). Quantification Of Tumour Angiogenesis Using Pattern Recognition. University of Heidelberg

Leue, C (1999). Quantitative Analyse von NOx - Emissionen aus GOME Satellitenbildfolgen. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg

Leue, C, Wenig, M, Wagner, T, Klimm, O, Platt, U and Jähne, B (2001). Quantitative analysis of NO$_x$ emissions from Global Ozone Monitoring Experiment satellite image sequences. J. Geophys. Res. 106 5493--5505

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

Andres, B, Köthe, U, Bonea, A, Nadler, B and Hamprecht, F A (2009). Quantitative Assessment of Image Segmentation Quality by Random Walk Relaxation Times. Pattern Recognition. 31st DAGM Symposium, Jena, Germany, September 9-11, 2009. Proceedings. Springer. 5748 502-511

Technical Report (3.08 MB)

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

Leue, C, Wenig, M, Jähne, B and Platt, U (1998). Quantitative observation of biomass-burning plumes from GOME. ESA Publications EOQ. 58 33--35. http://esapub.esrin.esa.it/eoq/eoq58

Barron, J L and Spies, H (2000). Quantitative regularized range flow. Vision Interface. 203--210

R

Haußecker, H, Jähne, B, Geißler, P and Haußecker, H (1999). Radiation. Handbook of Computer Vision and Applications. Academic Press. 1: Sensors and Imaging 7--35

Haußecker, H and Jähne, B (2000). Radiation and illumination. Computer Vision and Applications - A Guide for Students and Practitioners. Academic Press. 11--52

Erz, M and Jähne, B (2009). Radiometric and spectrometric calibrations, and distance noise measurement of TOF cameras. 3rd Workshop on Dynamic 3-D Imaging. Springer. 5742 28--41

Gröning, (2003). Radiometrische Kalibrierung und Charakterisierung von CCD- uund CMOS-Bildsensoren und Monokulares 3D-Tracking in Echtzeit. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg. http://www.ub.uni-heidelberg.de/archiv/3589

Haußecker, H, Jähne, B, Geißler, P and Haußecker, H (1999). Radiometry of imaging. Handbook of Computer Vision and Applications. Academic Press. 1: Sensors and Imaging 103--135

Haußecker, H and Jähne, B (2000). Radiometry of imaging. Computer Vision and Applications - A Guide for Students and Practitioners. Academic Press. 85--109

Massiceti, D, Krull, A, Brachmann, E, Rother, C and Torr, P H S (2017). Random Forests versus Neural Networks − What's best for camera location

Eigenstetter, A, Takami, M and Ommer, B (2014). Randomized Max-Margin Compositions for Visual Recognition. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. IEEE. 3590--3597

Technical Report (8.01 MB)

Spies, H, Jähne, B and Barron, J L (2002). Range flow estimation.. Computer Vision and Image Understanding. 85 209--231

Schmidt, M, Jehle, M and Jähne, B (2008). Range flow estimation based on photonic mixing device data. Int. J. Intelligent Systems Technologies and Applications. 5 380--392

Schmidt, M, Jehle, M and Jähne, B (2007). Range flow estimation based on photonic mixing device data. Proc.\ Dyn3D Workshop, Heidelberg, Sept. 11, 2007. ZESS, Univ.\ Siegen

Weickert, J and Schnörr, C (1999). Räumlich–zeitliche Berechnung des optischen Flusses mit nichtlinearen flussabhängigen Glattheitstermen. Mustererkennung 1999. Springer. 317–324

Strzodka, R and Garbe, C S (2004). Real-time motion estimation and visualization on graphics cards. Proceedings IEEE Visualization 2004. 545--552

Bruhn, A, Weickert, J, Feddern, C, Kohlberger, T and Schnörr, C (2003). Real-Time Optic Flow Computation with Variational Methods. Proc. Computer Analysis of Images and Patterns (CAIP'03). Springer. 2756 222-229

Hosseini Jafari, O and Yang, M Ying (2016). Real-time RGB-D based template matching pedestrian detection. Proceedings - IEEE International Conference on Robotics and Automation. 2016-June 5520–5527

Wiehler, K, Grigat, R –R, Heers, J, Schnörr, C and Stiehl, H –S (1998). Real–Time Adaptive Smoothing with a 1D Nonlinear Relaxation Network in Analogue VLSI Technology. Mustererkennung 1998. Springer, Heidelberg

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