Publications

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Haußecker, H, Jähne, B, Geißler, P and Haußecker, H (1999). Illumination sources and techniques. Handbook of Computer Vision and Applications. Academic Press. 1: Sensors and Imaging 137--162
Haußecker, H, Jähne, B and Jähne, B (1995). In situ measurements of the air-sea gas transfer rate during the MBL/CoOP west coast experiment. Air-Water Gas Transfer - Selected Papers from the Third International Symposium on Air-Water Gas Transfer. AEON. 775--784
Haußecker, H, Spies, H, Jähne, B, Geißler, P and Haußecker, H (1999). Motion. Handbook of Computer Vision and Applications. Academic Press. 2: Signal Processing and Pattern Recognition 309--396
Haußecker, (1993). Mehrgitter-Bewegungssegmentierung In Bildfolgen Mit Anwendung Zur Detektion Von Sedimentverlagerungen. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg
Haußecker, H, Jähne, B and Köhler, H - J (1995). Effiziente Filterstrukturen auf Mehrgitter-Datenstrukturen. Bildverarbeitung'95 - Forschen, Entwickeln, Anwenden. Technische Akademie Esslingen. 43--57
Haußecker, H, Tizhoosh, H R and Jähne, B (2000). Fuzzy image processing. Computer Vision and Applications - A Guide for Students and Practitioners. Academic Press. 541--576
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 (1996). A tensor approach for local structure analysis in multi-dimensional images. 3D Image Analysis and Synthesis. 171--178
Haußecker, H, Shear, R, Melville, W K and Jähne, B (1995). Horizontal and vertical spatial structures of turbulence beneath short wind waves. IAPSO Proceedings, XXI General Assembly, Honolulu, Hawai, August 1995, PS-10 Spatial Structure of Short Ocean Waves. 384
Haußecker, (1996). Messung und Simulation von kleinskaligen Austauschvorgängen an der Ozeanoberfläche mittels Thermographie. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg
Haußmann, M, Hamprecht, F A and Kandemir, M (2019). Deep Active Learning with Adaptive Acquisition. IJCAI. Proceedings, in press
Haußmann, M, Hamprecht, F A and Kandemir, M (2019). Sampling-Free Variational Inference of Bayesian Neural Networks by Variance Backpropagation. UAI. Proceedings, in press
Haußmann, (2016). Weakly Supervised Detection With Gaussian Processes. University of Heidelberg
Haußmann, M, Gerwinn, S and Kandemir, M (2019). Bayesian Prior Networks with PAC Training. arXiv preprint arXiv:1906.00816
Haußmann, M, Hamprecht, F A and Kandemir, M (2017). Variational Bayesian Multiple Instance Learning with Gaussian Processes. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 6570-6579PDF icon Technical Report (1.29 MB)
Hayn, M, Beirle, S, Hamprecht, F A, Platt, U, Menze, B H and Wagner, T (2009). Analysing spatio-temporal patterns of the global NO2-distribution retrieved frome GOME satellite observations using a generalized additive model. Atmospheric Chemistry and Physics. 9 9367-9398PDF icon Technical Report (2.52 MB)
Hayn, M (2007). Statistical Analysis Of Spatio-Temporal Patterns In Global Nox Satellite Data. University of Heidelberg
Heck, H (2011). Bildverarbeitendes Verfahren Zur Detektion Und Vermessung Von Luftblasen An Der Wasseroberfläche Eines Blasentanks. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg
Heck, D (2004). Proximity Graphs For Nonlinear Dimension Reduction. University of Heidelberg
Heers, J, Schnörr, C and Stiehl, H S (2001). Globally--Convergent Iterative Numerical Schemes for Non--Linear Variational Image Smoothing and Segmentation on a Multi--Processor Machine. IEEE Trans.~Image Proc. 10 852--864
Heers, J, Schnörr, C and Stiehl, H S (1998). Parallele und global konvergente iterative Minimierung nichtlinearer Variationsansätze zur adaptiven Glättung und Segmentation von Bildern. Mustererkennung 1998. Springer
Heers, J, Schnörr, C and Stiehl, H S (1998). Investigation of Parallel and Globally Convergent Iterative Schemes for Nonlinear Variational Image Smoothing and Segmentation. Proc.~IEEE Int.~Conf.~Image Proc
Heers, J, Schnörr, C and Stiehl, H S (1998). A class of parallel algorithms for nonlinear variational image segmentation. Proc.~Noblesse Workshop on Non--Linear Model Based Image Analysis (NMBIA'98)
Heers, J, Schnörr, C and Stiehl, H S (1999). Investigating A Class Of Iterative Schemes And Their Parallel Implementation For Nonlinear Variational Image Smoothing And Segmentation. Comp.~Sci.~Dept., AB KOGS
Hehn, T (2017). A Probabilistic Approach To Learn Complex Differentiable Split Functions In Decision Trees Using Gradient Ascent. Heidelberg University
Hehn, T and Hamprecht, F A (2018). End-to-end Learning of Deterministic Decision Trees. German Conference on Pattern Recognition. Proceedings. Springer. LNCS 11269 612-627PDF icon Technical Report (1.4 MB)
Heikkonen, J, Koikkalainen, P and Schnörr, C (1994). Building Trajectories via Selforganization from Spatiotemporal Features. 12th Int. Conf. on Pattern Recognition
Heiler, M and Schnörr, C (2006). Learning Sparse Representations by Non-Negative Matrix Factorization and Sequential Cone Programming. J.~Mach.~Learning Res. 7 1385--1407. http://www.cvgpr.uni-mannheim.de/Publications
Heiler, M and Schnörr, C (2003). Natural Statistics for Natural Image Segmentation. Proc.~IEEE Int.~Conf.~Computer Vision (ICCV 2003). 1259-1266
Heiler, M and Schnörr, C (2006). Controlling Sparseness in Non-negative Tensor Factorization. Computer Vision -- ECCV 2006. Springer. 3951 56-67PDF icon Technical Report (568.86 KB)
Heiler, M and Schnörr, C (2005). Reverse-Convex Programming for Sparse Image Codes. Proc.~Int.~Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR'05). Springer. 3757 600-616
Heiler, M, Keuchel, J and Schnörr, C (2005). Semidefinite Clustering for Image Segmentation with A-priori Knowledge. Pattern Recognition, Proc.~27th DAGM Symposium. Springer. 3663 309--317
Heiler, M and Schnörr, C (2005). Learning Sparse Image Codes by Convex Programming. Proc.~Tenth IEEE Int.~Conf.~Computer Vision (ICCV'05). 1667-1674
Heiler, M, Cremers, D and Schnörr, C (2001). Efficient Feature Subset Selection For Support Vector Machines. Dept.~Math.~and Comp.~Science
Heiler, M and Schnörr, C (2005). Natural Image Statistics for Natural Image Segmentation. Int.~J.~Comp.~Vision. 63 5--19

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