| Cereals-cost-effective region-based active learning for semantic segmentation R Mackowiak, P Lenz, O Ghori, F Diego, O Lange, C Rother arXiv preprint arXiv:1810.09726, 2018 | 130 | 2018 |
| Cost efficient gradient boosting S Peter, F Diego, FA Hamprecht, B Nadler Advances in neural information processing systems 30, 2017 | 71 | 2017 |
| Sparse Space-Time Deconvolution for Calcium Image Analysis F Diego, FA Hamprecht Neural Information Processing Signals (NIPS), 2014 | 60* | 2014 |
| Sparse Space-Time Deconvolution for Calcium Image Analysis FD Andilla, FA Hamprecht Neural Information Processing Signals (NIPS), 2014 | 60* | 2014 |
| Learning to forecast pedestrian intention from pose dynamics O Ghori, R Mackowiak, M Bautista, N Beuter, L Drumond, F Diego, ... 2018 IEEE Intelligent Vehicles Symposium (IV), 1277-1284, 2018 | 57 | 2018 |
| Video alignment for change detection F Diego, D Ponsa, J Serrat, AM López IEEE Transactions on Image Processing 20 (7), 1858-1869, 2010 | 57 | 2010 |
| Voice conversion of non-aligned data using unit selection H Duxans, D Erro, J Pérez, F Diego, A Bonafonte, A Moreno TC-STAR WSST, 2006 | 45 | 2006 |
| Joint spatio-temporal alignment of sequences F Diego, J Serrat, AM López IEEE Transactions on Multimedia 15 (6), 1377-1387, 2013 | 38 | 2013 |
| Road geometry classification by adaptive shape models JM Alvarez, T Gevers, F Diego, AM Lopez IEEE Transactions on Intelligent Transportation Systems 14 (1), 459-468, 2012 | 38 | 2012 |
| Automated identification of neuronal activity from calcium imaging by sparse dictionary learning F Diego, S Reichinnek, M Both, FA Hamprecht 2013 IEEE 10th International Symposium on Biomedical Imaging, 1058-1061, 2013 | 36 | 2013 |
| Inter-operability and orchestration in heterogeneous cloud/edge resources: The accordion vision I Korontanis, K Tserpes, M Pateraki, L Blasi, J Violos, F Diego, E Marin, ... Proceedings of the 1st Workshop on Flexible Resource and Application …, 2020 | 32 | 2020 |
| Tracking indistinguishable translucent objects over time using weakly supervised structured learning L Fiaschi, F Diego, K Gregor, M Schiegg, U Koethe, M Zlatic, ... Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2014 | 31 | 2014 |
| Security in Cloud-Native Services: A Survey T Theodoropoulos, L Rosa, C Benzaid, P Gray, E Marin, A Makris, ... Journal of Cybersecurity and Privacy 3 (4), 758-793, 2023 | 29 | 2023 |
| Sparse convolutional coding for neuronal assembly detection S Peter, E Kirschbaum, M Both, L Campbell, B Harvey, C Heins, ... Advances in Neural Information Processing Systems 30, 2017 | 27 | 2017 |
| Learning multi-level sparse representations F Diego Andilla, FA Hamprecht Advances in Neural Information Processing Systems 26, 2013 | 25 | 2013 |
| Vision-based road detection via on-line video registration F Diego, JM Alvarez, J Serrat, AM López 13th International IEEE Conference on Intelligent Transportation Systems …, 2010 | 20 | 2010 |
| Variational Weakly Supervised Gaussian Processes. M Kandemir, M Haussmann, F Diego, KT Rajamani, J Van Der Laak, ... BMVC, 71.1-71.12, 2016 | 16 | 2016 |
| Synchronization of video sequences from free-moving cameras J Serrat, F Diego, F Lumbreras, JM Álvarez Iberian Conference on Pattern Recognition and Image Analysis, 620-627, 2007 | 14 | 2007 |
| Unsupervised representation learning by discovering reliable image relations T Milbich, O Ghori, F Diego, B Ommer Pattern Recognition 102, 107107, 2020 | 10 | 2020 |
| Istdeco: In situ transcriptomics decoding by deconvolution A Andersson, F Diego, FA Hamprecht, C Wählby bioRxiv, 2021.03. 01.433040, 2021 | 9 | 2021 |
Fred A. HamprechtProfessor, Heidelberg UniversityVerified email at iwr.uni-heidelberg.de
