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Gianniotis, N and Tiño, P (2009). Visualization of Structured Data via Generative Probabilistic Modeling. Pattern Recognition. Springer. 5400 118-137

Gianniotis, N, Tiño, P, Spreckley, S and Raychaudhury, S (2009). Topographic Mapping of Astronomical Light Curves via a Physically Inspired Probabilistic Model. Proceedings of ICANN 2009. 567-576

Giebel, J, Gavrila, D M and Schnörr, C (2004). A Bayesian Framework for Multi-cue 3D Object Tracking. Computer Vision – ECCV 2004. Springer. 3024 241-252

Glas, M (2012). Methoden zur sechsdimensionalen Objektlageerkennung aus Tiefenbildern. IWR, Fakultät für Physik und Astronomie, Univ. Heidelberg. Dissertation

Glas, M (2012). Methoden zur sechsdimensionalen Objektlageerkennung aus Tiefenbildern. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg. http://www.ub.uni-heidelberg.de/archiv/13581

Gleisinger, R (2000). Entwurf Und Implementation Eines Objektorientierten Inspektors Für Multidimensionale Wissenschaftliche Daten. Lehrgebiet praktische Informatik, Fachbereich Informatik Fernuniversität Hagen

Gliß, (2010). Entwicklung Und Implementierung Eines Cavity-Enhanced-Spektrometers Am Wind-Wellen-Kanal. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg

Glocker, B, T. Heibel, H, Navab, N, Kohli, P and Rother, C (2010). TriangleFlow: Optical flow with triangulation-based higher-order likelihoods. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6313 LNCS 272–285. http://vision.middlebury.edu/flow/

Goldlücke, B, Strekalovskiy, E and Cremers, D (2012). The Natural Vectorial Total Variation which Arises from Geometric Measure Theory. SIAM Journal on Imaging Sciences. 5 537-563

Goldlücke, B, Aubry, M, Kolev, K and Cremers, D (2014). A super-resolution framework for high-accuracy multiview reconstruction. Int. J. Comp. Vision. 106 172--191

Goldlücke, B, Strekalovskiy, E and Cremers, D (2013). Tight convex relaxations for vector-valued labeling. SIAM Journal on Imaging Sciences

Goldlücke, B, Strekalovskiy, E and Cremers, D (2012). The natural vectorial total variation which arises from geometric measure theory. SIAM Journal on Imaging Sciences

Goldlücke, B and Wanner, S (2013). The Variational Structure of Disparity and Regularization of 4D Light Fields. IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Gonzalez-Alvarado, D, Zeilmann, A and Schnörr, C (2021). Assignment Flows and Nonlocal PDEs on Graphs. GCPR, in press

Görlitz, (2007). Modern Concepts for Semi-Supervised Learning and Multidimensional Image Processing. University of Heidelberg

Görlitz, L, Hamprecht, F A and Staudacher, M (2009). Allocation of particles to development processes. Patent

Technical Report (406.7 KB)

Görlitz, L, Menze, B H, Kelm, B Michael and Hamprecht, F A (2009). Processing Spectral Data. Surface and Interface Analysis. 41 636-644

Technical Report (4.17 MB)

Görlitz, L, Menze, B H, Weber, M - A and Kelm, B Michael (2007). Semi-Supervised Tumor Detection in MRSI With Discriminative Random Fields. Pattern Recognition. Springer. 4713 224-233

Technical Report (872.46 KB)

Görlitz, L, Singh, M and Schützbach, P (2007). Schnelle 3D-Vermessung von Partikeln in Rasterelektronenmiskroskopen mit Hilfe eines Rücksteuerdetektors

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

Gosch, C (2009). Contour Methods for View Point Tracking. University of Heidelberg. http://www.ub.uni-heidelberg.de/archiv/9684/

Gosch, C, Fundana, K, Heyden, A and Schnörr, C (2008). View Point Tracking of Rigid Object Based on Shape Sub-Manifolds. Computer Vision – ECCV 2008. Springer. 5302 251–263

Gosch, C, Fundana, K, Heyden, A and Schnörr, C (2008). View Point Tracking of Rigid Object Based on Shape Sub-Manifolds. Computer Vision -- ECCV 2008. Springer. 5302 251--263

Technical Report (523.17 KB)

Gottfried, J - M, Nair, R, Meister, S, Garbe, C S and Kondermann, D (2014). Time of flight motion compensation revisited. International Conference on Image Processing, ICIP 2014

Götz, (1999). Bildverarbeitungsalgorithmen In Der Fluoreszenzmikroskopie. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg

Greis, J (2009). Semi-Automatic Analysis Of High-Information-Content Neurobiological Image Data. University of Heidelberg

Griessinger, M (2008). Oject Detection With Generic Features: An Application To Sted Microscopy. University of Heidelberg

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

Gröning, (1996). Mehrgitterbewegungssegmentierung Und Messungen Am Grossen Simulationstank Zur Bestimmung Von Sedimentverlagerungen. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg

Großkinsky, (2019). Synaptic Cleft Prediction On Electron Microsope Images. Heidelberg University

Grosser, K - H (1989). Entwicklung Eines Verfahrens Zur Optischen Messung Der Wellenhöhe Von Wasseroberflächenwellen. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg

Grützmann, (2009). Reconstruction of Moving Surfaces of Revolution from Sparse 3-D Measurements using a Stereo Camera and Structured Light. IWR, Fakultät für Mathematik und Informatik, Univ.\ Heidelberg. http://www.ub.uni-heidelberg.de/archiv/10162

Gulshan, V, Rother, C, Criminisi, A, Blake, A and Zisserman, A (2010). Geodesic star convexity for interactive image segmentation. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 3129–3136

Güssefeld, B, Kondermann, D, Schwartz, C and Klein, R (2014). Are reflectance field renderings appropriate for optical flow evaluation?. International Conference on Image Processing, ICIP 2014

Güssefeld, B, Honauer, K and Kondermann, D (2016). Creating Feasible Reflectance Data for Synthetic Optical Flow Datasets. Advances in Visual Computing - 12th International Symposium, {ISVC} 2016, Las Vegas, NV, USA, December 12-14, 2016, Proceedings, Part {I}

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