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Kai Krajsek
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2020 – today
- 2021
- [c21]Stefan Kesselheim, Andreas Herten
, Kai Krajsek, Jan Ebert, Jenia Jitsev, Mehdi Cherti, Michael Langguth, Bing Gong
JUWELS Booster - A Supercomputer for Large-Scale AI Research. ISC Workshops 2021: 453-468 - [i2]Stefan Kesselheim, Andreas Herten, Kai Krajsek, Jan Ebert, Jenia Jitsev, Mehdi Cherti, Michael Langguth, Bing Gong, Scarlet Stadtler, Amirpasha Mozaffari, Gabriele Cavallaro, Rocco Sedona, Alexander Schug, Alexandre Strube, Roshni Kamath, Martin G. Schultz, Morris Riedel, Thomas Lippert:
JUWELS Booster - A Supercomputer for Large-Scale AI Research. CoRR abs/2108.11976 (2021) - 2020
- [c20]Markus Götz
HeAT - a Distributed and GPU-accelerated Tensor Framework for Data Analytics. IEEE BigData 2020: 276-287 - [c19]Alper Yegenoglu
Ensemble Kalman Filter Optimizing Deep Neural Networks: An Alternative Approach to Non-performing Gradient Descent. LOD (2) 2020: 78-92 - [i1]Markus Götz
HeAT - a Distributed and GPU-accelerated Tensor Framework for Data Analytics. CoRR abs/2007.13552 (2020)
2010 – 2019
- 2016
- [j2]Kai Krajsek
A Riemannian Bayesian Framework for Estimating Diffusion Tensor Images. Int. J. Comput. Vis. 120(3): 272-299 (2016) - [c18]Vasileios Zografos, Kai Krajsek, Bjoern H. Menze
An Online Algorithm for Efficient and Temporally Consistent Subspace Clustering. ACCV (1) 2016: 353-368 - 2015
- [b1]Kai Krajsek:
Probabilistic models and estimation: theoretical concepts for variational approaches to computer vision. Goethe University Frankfurt am Main, 2015, pp. 1-287 - 2014
- [c17]Christian Heinemann, Freddie Åström, George Baravdish, Kai Krajsek
Using Channel Representations in Regularization Terms - A Case Study on Image Diffusion. VISAPP (1) 2014: 48-55 - [c16]Kai Krajsek
Likelihood Functions for Errors-in-variables Models - Bias-free Local Estimation with Minimum Variance. VISAPP (3) 2014: 270-279 - 2012
- [c15]Kai Krajsek, Hanno Scharr:
A Riemannian approach for estimating orientation distribution function (ODF) images from high-angular resolution diffusion imaging (HARDI). CVPR 2012: 1019-1026 - [p1]Hanno Scharr
A Short Introduction to Diffusion-Like Methods. Mathematical Methods for Signal and Image Analysis and Representation 2012: 1-30 - 2011
- [c14]Kai Krajsek
An Estimation Theoretical Approach to Ambrosio-Tortorelli Image Segmentation. DAGM-Symposium 2011: 41-50 - 2010
- [c13]Kai Krajsek
Diffusion filtering without parameter tuning: Models and inference tools. CVPR 2010: 2536-2543
2000 – 2009
- 2009
- [c12]Kai Krajsek, Marion I. Menzel
Riemannian Bayesian estimation of diffusion tensor images. ICCV 2009: 2327-2334 - 2008
- [j1]Tobias Preusser, Hanno Scharr
Building Blocks for Computer Vision with Stochastic Partial Differential Equations. Int. J. Comput. Vis. 80(3): 375-405 (2008) - [c11]Kai Krajsek, Rudolf Mester
Statistically Optimal Averaging for Image Restoration and Optical Flow Estimation. DAGM-Symposium 2008: 466-475 - [c10]Kai Krajsek, Marion I. Menzel, Michael Zwanger, Hanno Scharr
Riemannian Anisotropic Diffusion for Tensor Valued Images. ECCV (4) 2008: 326-339 - 2007
- [c9]Holger Friedrich, David Dederscheck, Kai Krajsek, Rudolf Mester:
View-Based Robot Localization Using Spherical Harmonics: Concept and First Experimental Results. DAGM-Symposium 2007: 21-31 - [c8]Kai Krajsek, Rudolf Mester:
Bayesian Model Selection for Optical Flow Estimation. DAGM-Symposium 2007: 142-151 - [c7]Jakub K. Kominiarczuk, Kai Krajsek, Rudolf Mester
Highly Accurate Orientation Estimation using Steerable Filters. ICIP (5) 2007: 277-280 - 2006
- [c6]Kai Krajsek, Rudolf Mester:
The Edge Preserving Wiener Filter for Scalar and Tensor Valued Images. DAGM-Symposium 2006: 91-100 - [c5]Kai Krajsek, Rudolf Mester
A Maximum Likelihood Estimator for Choosing the Regularization Parameters in Global Optical Flow Methods. ICIP 2006: 1081-1084 - [c4]Kai Krajsek, Rudolf Mester:
An unified theory for steerable and quadrature filters. VISAPP (1) 2006: 48-55 - [c3]Kai Krajsek, Rudolf Mester
A Unified Theory for Steerable and Quadrature Filters. VISIGRAPP (Selected Papers) 2006: 201-214 - 2005
- [c2]Kai Krajsek, Rudolf Mester:
Signal and Noise Adapted Filters for Differential Motion Estimation. DAGM-Symposium 2005: 476-484 - 2004
- [c1]Kai Krajsek, Rudolf Mester:
Wiener-Optimized Discrete Filters for Differential Motion Estimation. IWCM 2004: 30-41
Coauthor Index
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