Publications

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Haußecker, H, Schimpf, U and Jähne, B (1998). Measurements of the air-sea gas transfer and its mechanisms by active and passive thermography. Proc. IEEE International Geoscience and Remote Sensing Symposium IGARSS '98. 1 484--486 vol.1
Haußecker, H and Jähne, B (2000). Radiometry of imaging. Computer Vision and Applications - A Guide for Students and Practitioners. Academic Press. 85--109
Haußecker, H and Jähne, B (1994). In-situ measurements of the air-sea gas transfer using heat as a proxy tracer. Proc. 2nd Inter. Conf. on Air-Sea Interaction and on Meteorology and Oceanography of the Coastal Zone, Lisbon, 22.--27. September 1994
Haußecker, H, Spies, H and Jähne, B (1998). Tensor-based image sequence processing techniques for the study of dynamical processes. Proc. Intern. Symp. On Real-time Imaging and Dynamic Analysis. International Society of Photogrammetry and Remote Sensing, ISPRS, Commision V. 704--711
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 Fleet, D J (2001). Computing optical flow with physical models of brightness variation. IEEE Trans. Pattern Analysis Machine Intelligence. 23 661--673
Haußecker, H, Schimpf, U, Garbe, C S and Jähne, B (2002). Physics from IR image sequences: Quantitative analysis of transport models and parameters of air-sea gas transfer. Gas Transfer at Water Surfaces. American Geophysical Union. 127 103--108
Haußecker, H and Jähne, B (2000). Radiation and illumination. Computer Vision and Applications - A Guide for Students and Practitioners. Academic Press. 11--52
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)
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
Hayn, M (2007). Statistical Analysis Of Spatio-Temporal Patterns In Global Nox Satellite Data. University of Heidelberg
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)
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 (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
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
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)
Hehn, T (2017). A Probabilistic Approach To Learn Complex Differentiable Split Functions In Decision Trees Using Gradient Ascent. Heidelberg University
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). 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
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
Heinz, G (1986). Messung Der Diffusionskonstanten Von In Wasser Gelösten Gasen Mit Einem Modifizierten Barrerverfahren. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg
Heitz, D, Mémin, E and Schnörr, C (2010). Variational fluid flow measurements from image sequences: synopsis and perspectives. Exp.~Fluids. 48 369-393PDF icon Technical Report (1.91 MB)

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