Data Mining: Practical machine learning tools and techniques IH Witten, E Frank, MA Hall, CJ Pal Morgan Kaufmann, 2016 | 50894* | 2016 |
Brain tumor segmentation with deep neural networks M Havaei, A Davy, D Warde-Farley, A Biard, A Courville, Y Bengio, C Pal, ... Medical image analysis 35, 18-31, 2017 | 3657 | 2017 |
The importance of skip connections in biomedical image segmentation M Drozdzal, E Vorontsov, G Chartrand, S Kadoury, C Pal International workshop on deep learning in medical image analysis …, 2016 | 1350 | 2016 |
Describing videos by exploiting temporal structure L Yao, A Torabi, K Cho, N Ballas, C Pal, H Larochelle, A Courville Proceedings of the IEEE international conference on computer vision, 4507-4515, 2015 | 1338 | 2015 |
Theano: A Python framework for fast computation of mathematical expressions R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, N Ballas, ... arXiv e-prints, arXiv: 1605.02688, 2016 | 1189* | 2016 |
Learning conditional random fields for stereo D Scharstein, C Pal 2007 IEEE conference on computer vision and pattern recognition, 1-8, 2007 | 1169 | 2007 |
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 | 1168 | 2023 |
Deep learning: a primer for radiologists G Chartrand, PM Cheng, E Vorontsov, M Drozdzal, S Turcotte, CJ Pal, ... Radiographics 37 (7), 2113-2131, 2017 | 1157 | 2017 |
Deep Complex Networks C Trabelsi, Y Bilaniuk, Olexa, Zhang, D Serdyuk, S Subramanian, ... ICLR 2018, 2018 | 1022 | 2018 |
Delving deeper into convolutional networks for learning video representations N Ballas, L Yao, C Pal, A Courville ICLR 2016, 2015 | 872 | 2015 |
Activity recognition using the velocity histories of tracked keypoints R Messing, C Pal, H Kautz 2009 IEEE 12th international conference on computer vision, 104-111, 2009 | 677 | 2009 |
ISLES 2015-A public evaluation benchmark for ischemic stroke lesion segmentation from multispectral MRI O Maier, BH Menze, J Von der Gablentz, L Häni, MP Heinrich, M Liebrand, ... Medical image analysis 35, 250-269, 2017 | 519 | 2017 |
Emonets: Multimodal deep learning approaches for emotion recognition in video SE Kahou, X Bouthillier, P Lamblin, C Gulcehre, V Michalski, K Konda, ... Journal on Multimodal User Interfaces 10, 99-111, 2016 | 510 | 2016 |
Real-time preview for panoramic images P Baudisch, C Pal, E Rudolph, D Steedly, R Szeliski, D Tan, ... US Patent 7,424,218, 2008 | 505 | 2008 |
Recurrent neural networks for emotion recognition in video S Ebrahimi Kahou, V Michalski, K Konda, R Memisevic, C Pal Proceedings of the 2015 ACM on international conference on multimodal …, 2015 | 473 | 2015 |
Combining modality specific deep neural networks for emotion recognition in video SE Kahou, C Pal, X Bouthillier, P Froumenty, Ç Gülçehre, R Memisevic, ... Proceedings of the 15th ACM on International conference on multimodal …, 2013 | 438 | 2013 |
Movie description A Rohrbach, A Torabi, M Rohrbach, N Tandon, C Pal, H Larochelle, ... International Journal of Computer Vision 123, 94-120, 2017 | 399 | 2017 |
Towards deep conversational recommendations R Li, S Kahou, H Schulz, V Michalski, L Charlin, C Pal NeurIPS 2018, arXiv preprint arXiv:1812.07617, 2018 | 397 | 2018 |
Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning S Subramanian, A Trischler, Y Bengio, C Pal ICLR 2018, (OpenReview 2017), 2018 | 396 | 2018 |
Zoneout: Regularizing rnns by randomly preserving hidden activations D Krueger, T Maharaj, J Kramár, M Pezeshki, N Ballas, NR Ke, A Goyal, ... ICLR 2017, 2016 | 386 | 2016 |