| Analysis operator learning and its application to image reconstruction S Hawe, M Kleinsteuber, K Diepold IEEE Transactions on Image Processing 22 (6), 2138-2150, 2013 | 184 | 2013 |
| Joint matrices decompositions and blind source separation: A survey of methods, identification, and applications G Chabriel, M Kleinsteuber, E Moreau, H Shen, P Tichavsky, A Yeredor IEEE Signal Processing Magazine 31 (3), 34-43, 2014 | 158 | 2014 |
| Separable dictionary learning S Hawe, M Seibert, M Kleinsteuber Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2013 | 146 | 2013 |
| Dense disparity maps from sparse disparity measurements S Hawe, M Kleinsteuber, K Diepold 2011 International Conference on Computer Vision, 2126-2133, 2011 | 131 | 2011 |
| A joint intensity and depth co-sparse analysis model for depth map super-resolution M Kiechle, S Hawe, M Kleinsteuber Proceedings of the IEEE international conference on computer vision, 1545-1552, 2013 | 126 | 2013 |
| Cash flow prediction: MLP and LSTM compared to ARIMA and Prophet H Weytjens, E Lohmann, M Kleinsteuber Electronic Commerce Research 21 (2), 371-391, 2021 | 115 | 2021 |
| Compositional learning of image-text query for image retrieval MU Anwaar, E Labintcev, M Kleinsteuber Proceedings of the IEEE/CVF Winter conference on Applications of Computer …, 2021 | 107 | 2021 |
| Sample complexity of dictionary learning and other matrix factorizations R Gribonval, R Jenatton, F Bach, M Kleinsteuber, M Seibert IEEE Transactions on Information Theory 61 (6), 3469-3486, 2015 | 107 | 2015 |
| pROST: a smoothed -norm robust online subspace tracking method for background subtraction in video F Seidel, C Hage, M Kleinsteuber Machine vision and applications 25 (5), 1227-1240, 2014 | 93 | 2014 |
| Network volume anomaly detection and identification in large-scale networks based on online time-structured traffic tensor tracking H Kasai, W Kellerer, M Kleinsteuber IEEE transactions on network and service management 13 (3), 636-650, 2016 | 80 | 2016 |
| Combining knowledge modeling and machine learning for alarm root cause analysis L Abele, M Anic, T Gutmann, J Folmer, M Kleinsteuber, B Vogel-Heuser IFAC Proceedings Volumes 46 (9), 1843-1848, 2013 | 71 | 2013 |
| Improving non-profiled attacks on exponentiations based on clustering and extracting leakage from multi-channel high-resolution EM measurements R Specht, J Heyszl, M Kleinsteuber, G Sigl International Workshop on Constructive Side-Channel Analysis and Secure …, 2015 | 49 | 2015 |
| Blind source separation with compressively sensed linear mixtures M Kleinsteuber, H Shen IEEE signal processing letters 19 (2), 107-110, 2011 | 47 | 2011 |
| Local convergence analysis of FastICA and related algorithms H Shen, M Kleinsteuber, K Huper IEEE Transactions on Neural Networks 19 (6), 1022-1032, 2008 | 45 | 2008 |
| Robust PCA and subspace tracking from incomplete observations using -surrogates C Hage, M Kleinsteuber Computational Statistics 29 (3), 467-487, 2014 | 44 | 2014 |
| Reconstructible nonlinear dimensionality reduction via joint dictionary learning X Wei, H Shen, Y Li, X Tang, F Wang, M Kleinsteuber, YL Murphey IEEE transactions on neural networks and learning systems 30 (1), 175-189, 2018 | 43 | 2018 |
| Glyphboard: Visual exploration of high-dimensional data combining glyphs with dimensionality reduction D Kammer, M Keck, T Gründer, A Maasch, T Thom, M Kleinsteuber, ... IEEE transactions on visualization and computer graphics 26 (4), 1661-1671, 2020 | 38 | 2020 |
| Rolling stiefel manifolds K Hüper, M Kleinsteuber, F Silva Leite International Journal of Systems Science 39 (9), 881-887, 2008 | 36 | 2008 |
| Model-based learning of local image features for unsupervised texture segmentation M Kiechle, M Storath, A Weinmann, M Kleinsteuber IEEE Transactions on Image Processing 27 (4), 1994-2007, 2018 | 34 | 2018 |
| A rgb/nir data set for evaluating dehazing algorithms J Lüthen, J Wörmann, M Kleinsteuber, J Steurer Electronic Imaging 29, 79-87, 2017 | 28 | 2017 |
Hao Shenfortiss GmbH/TUM確認したメール アドレス: tum.de
