| A parallel neural network approach to prediction of Parkinson’s Disease F Åström, R Koker Expert Systems with Applications 38 (10), 12470-12474, 2011 | 173 | 2011 |
| Image labeling by assignment F Åström, S Petra, B Schmitzer, C Schnörr Journal of Mathematical Imaging and Vision 58, 211-238, 2017 | 64 | 2017 |
| Numerical reconstruction of brain tumours R Jaroudi, G Baravdish, BT Johansson, F Åström Inverse Problems in Science and Engineering 27 (3), 278-298, 2019 | 19 | 2019 |
| Image labeling based on graphical models using wasserstein messages and geometric assignment R Hühnerbein, F Savarino, F Åström, C Schnörr SIAM Journal on Imaging Sciences 11 (2), 1317-1362, 2018 | 18 | 2018 |
| On Backward p(x)-Parabolic Equations for Image Enhancement G Baravdish, O Svensson, F Åström Numerical Functional Analysis and Optimization 36 (2), 147-168, 2015 | 15 | 2015 |
| Numerical simulations in 3-dimensions of reaction–diffusion models for brain tumour growth R Jaroudi, F Åström, BT Johansson, G Baravdish International Journal of Computer Mathematics 97 (6), 1151-1169, 2020 | 14 | 2020 |
| On tensor-based PDEs and their corresponding variational formulations with application to color image denoising F Åström, G Baravdish, M Felsberg Computer Vision–ECCV 2012: 12th European Conference on Computer Vision …, 2012 | 14 | 2012 |
| A tensor variational formulation of gradient energy total variation F Åström, G Baravdish, M Felsberg Energy Minimization Methods in Computer Vision and Pattern Recognition: 10th …, 2015 | 11 | 2015 |
| Color persistent anisotropic diffusion of images F Åström, M Felsberg, R Lenz Image Analysis: 17th Scandinavian Conference, SCIA 2011, Ystad, Sweden, May …, 2011 | 10 | 2011 |
| Unsupervised label learning on manifolds by spatially regularized geometric assignment A Zern, M Zisler, F Åström, S Petra, C Schnörr Pattern Recognition: 40th German Conference, GCPR 2018, Stuttgart, Germany …, 2019 | 9 | 2019 |
| Source localization of reaction-diffusion models for brain tumors R Jaroudi, G Baravdish, F Åström, BT Johansson Pattern Recognition: 38th German Conference, GCPR 2016, Hannover, Germany …, 2016 | 9 | 2016 |
| Numerical integration of Riemannian gradient flows for image labeling F Savarino, R Hühnerbein, F Åström, J Recknagel, C Schnörr Scale Space and Variational Methods in Computer Vision: 6th International …, 2017 | 8 | 2017 |
| MAP image labeling using Wasserstein messages and geometric assignment F Åström, R Hühnerbein, F Savarino, J Recknagel, C Schnörr Scale Space and Variational Methods in Computer Vision: 6th International …, 2017 | 5 | 2017 |
| Graphical model parameter learning by inverse linear programming V Trajkovska, P Swoboda, F Åström, S Petra Scale Space and Variational Methods in Computer Vision: 6th International …, 2017 | 5 | 2017 |
| Targeted iterative filtering F Åström, M Felsberg, G Baravdish, C Lundström Scale Space and Variational Methods in Computer Vision: 4th International …, 2013 | 5 | 2013 |
| A geometric approach for color image regularization F Åström, C Schnörr Computer Vision and Image Understanding 165, 43-59, 2017 | 4 | 2017 |
| Mapping-based image diffusion F Åström, M Felsberg, G Baravdish Journal of Mathematical Imaging and Vision 57, 293-323, 2017 | 4 | 2017 |
| Image reconstruction by multilabel propagation M Zisler, F Åström, S Petra, C Schnörr Scale Space and Variational Methods in Computer Vision: 6th International …, 2017 | 4 | 2017 |
| On coupled regularization for non-convex variational image enhancement F Åström, C Schnorr 2015 3rd IAPR Asian Conference on Pattern Recognition (ACPR), 786-790, 2015 | 4 | 2015 |
| Extension of p-Laplace Operator for Image Denoising G Baravdish, Y Cheng, O Svensson, F Åström IFIP Conference on System Modeling and Optimization, 107-116, 2015 | 4 | 2015 |
