| Man vs. computer: Benchmarking machine learning algorithms for traffic sign recognition J Stallkamp, M Schlipsing, J Salmen, C Igel Neural networks 32, 323-332, 2012 | 2204 | 2012 |
| The liver tumor segmentation benchmark (lits) P Bilic, P Christ, HB Li, E Vorontsov, A Ben-Cohen, G Kaissis, A Szeskin, ... Medical image analysis 84, 102680, 2023 | 1881 | 2023 |
| The German traffic sign recognition benchmark: a multi-class classification competition J Stallkamp, M Schlipsing, J Salmen, C Igel The 2011 international joint conference on neural networks, 1453-1460, 2011 | 1831 | 2011 |
| Detection of traffic signs in real-world images: The German Traffic Sign Detection Benchmark S Houben, J Stallkamp, J Salmen, M Schlipsing, C Igel The 2013 international joint conference on neural networks (IJCNN), 1-8, 2013 | 1465 | 2013 |
| Empirical evaluation of the improved Rprop learning algorithms C Igel, M Hüsken Neurocomputing 50, 105-123, 2003 | 1067 | 2003 |
| Covariance matrix adaptation for multi-objective optimization C Igel, N Hansen, S Roth Evolutionary computation 15 (1), 1-28, 2007 | 1050 | 2007 |
| An introduction to restricted Boltzmann machines A Fischer, C Igel Iberoamerican congress on pattern recognition, 14-36, 2012 | 971 | 2012 |
| Deep feature learning for knee cartilage segmentation using a triplanar convolutional neural network A Prasoon, K Petersen, C Igel, F Lauze, E Dam, M Nielsen International conference on medical image computing and computer-assisted …, 2013 | 882 | 2013 |
| Training restricted Boltzmann machines: An introduction A Fischer, C Igel Pattern Recognition 47 (1), 25-39, 2014 | 745 | 2014 |
| Evolutionary tuning of multiple SVM parameters F Friedrichs, C Igel Neurocomputing 64, 107-117, 2005 | 715 | 2005 |
| Unsupervised deep learning applied to breast density segmentation and mammographic risk scoring M Kallenberg, K Petersen, M Nielsen, AY Ng, P Diao, C Igel, CM Vachon, ... IEEE transactions on medical imaging 35 (5), 1322-1331, 2016 | 564 | 2016 |
| Self-supervised speech representation learning: A review A Mohamed, H Lee, L Borgholt, JD Havtorn, J Edin, C Igel, K Kirchhoff, ... IEEE Journal of Selected Topics in Signal Processing 16 (6), 1179-1210, 2022 | 563 | 2022 |
| An unexpectedly large count of trees in the West African Sahara and Sahel M Brandt, CJ Tucker, A Kariryaa, K Rasmussen, C Abel, J Small, J Chave, ... Nature 587 (7832), 78-82, 2020 | 505 | 2020 |
| U-time: A fully convolutional network for time series segmentation applied to sleep staging M Perslev, M Jensen, S Darkner, PJ Jennum, C Igel Advances in neural information processing systems 32, 2019 | 411 | 2019 |
| U-Sleep: resilient high-frequency sleep staging M Perslev, S Darkner, L Kempfner, M Nikolic, PJ Jennum, C Igel NPJ digital medicine 4 (1), 72, 2021 | 348 | 2021 |
| Shark. C Igel, V Heidrich-Meisner, T Glasmachers Journal of machine learning research 9 (6), 2008 | 282 | 2008 |
| Early detection of Alzheimer's disease using M RI hippocampal texture L Sørensen, C Igel, N Liv Hansen, M Osler, M Lauritzen, E Rostrup, ... Human brain mapping 37 (3), 1148-1161, 2016 | 261 | 2016 |
| A computational efficient covariance matrix update and a (1+ 1)-CMA for evolution strategies C Igel, T Suttorp, N Hansen Proceedings of the 8th annual conference on Genetic and evolutionary …, 2006 | 242 | 2006 |
| Neuroevolution for reinforcement learning using evolution strategies C Igel The 2003 Congress on Evolutionary Computation, 2003. CEC'03. 4, 2588-2595, 2003 | 224 | 2003 |
| Active learning with support vector machines J Kremer, K Steenstrup Pedersen, C Igel Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 4 (4 …, 2014 | 214 | 2014 |
Mads NielsenProfessor of Computer Science, University of CopenhagenVerified email at diku.edu
