| Going deeper with convolutions C Szegedy, W Liu, Y Jia, P Sermanet, S Reed, D Anguelov, D Erhan, ... Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 25058 | 2015 |
| Ssd: Single shot multibox detector W Liu, D Anguelov, D Erhan, C Szegedy, S Reed, CY Fu, AC Berg European conference on computer vision, 21-37, 2016 | 10866 | 2016 |
| Intriguing properties of neural networks C Szegedy, W Zaremba, I Sutskever, J Bruna, D Erhan, I Goodfellow, ... arXiv preprint arXiv:1312.6199, 2013 | 5479 | 2013 |
| Show and tell: A neural image caption generator O Vinyals, A Toshev, S Bengio, D Erhan Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 3978 | 2015 |
| Why does unsupervised pre-training help deep learning? D Erhan, A Courville, Y Bengio, P Vincent Proceedings of the thirteenth international conference on artificial …, 2010 | 2334 | 2010 |
| Deep neural networks for object detection C Szegedy, A Toshev, D Erhan Advances in neural information processing systems, 2553-2561, 2013 | 1108 | 2013 |
| An empirical evaluation of deep architectures on problems with many factors of variation H Larochelle, D Erhan, A Courville, J Bergstra, Y Bengio Proceedings of the 24th international conference on Machine learning, 473-480, 2007 | 932 | 2007 |
| Scalable object detection using deep neural networks D Erhan, C Szegedy, A Toshev, D Anguelov Proceedings of the IEEE conference on computer vision and pattern …, 2014 | 916 | 2014 |
| Unsupervised pixel-level domain adaptation with generative adversarial networks K Bousmalis, N Silberman, D Dohan, D Erhan, D Krishnan Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 855 | 2017 |
| Visualizing higher-layer features of a deep network D Erhan, Y Bengio, A Courville, P Vincent University of Montreal 1341 (3), 1, 2009 | 819 | 2009 |
| Theano: A Python framework for fast computation of mathematical expressions R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, N Ballas, ... arXiv, arXiv: 1605.02688, 2016 | 701* | 2016 |
| Domain separation networks K Bousmalis, G Trigeorgis, N Silberman, D Krishnan, D Erhan Advances in neural information processing systems, 343-351, 2016 | 658 | 2016 |
| Challenges in representation learning: A report on three machine learning contests IJ Goodfellow, D Erhan, PL Carrier, A Courville, M Mirza, B Hamner, ... Neural Networks 64, 59-63, 2015 | 566 | 2015 |
| Show and tell: Lessons learned from the 2015 mscoco image captioning challenge O Vinyals, A Toshev, S Bengio, D Erhan IEEE transactions on pattern analysis and machine intelligence 39 (4), 652-663, 2016 | 516 | 2016 |
| The difficulty of training deep architectures and the effect of unsupervised pre-training D Erhan, PA Manzagol, Y Bengio, S Bengio, P Vincent Artificial Intelligence and Statistics, 153-160, 2009 | 445 | 2009 |
| Training deep neural networks on noisy labels with bootstrapping S Reed, H Lee, D Anguelov, C Szegedy, D Erhan, A Rabinovich arXiv preprint arXiv:1412.6596, 2014 | 427 | 2014 |
| Scalable, high-quality object detection C Szegedy, S Reed, D Erhan, D Anguelov, S Ioffe arXiv preprint arXiv:1412.1441, 2014 | 354 | 2014 |
| Very deep convolutional networks for large-scale image recognition S Karen, A Zisserman arXiv preprint arXiv:1409.1556 1 (2), 2014 | 345 | 2014 |
| Aggregate features and ADABOOST for music classification J Bergstra, N Casagrande, D Erhan, D Eck, B Kégl Machine learning 65 (2-3), 473-484, 2006 | 337 | 2006 |
| Zero-data learning of new tasks. H Larochelle, D Erhan, Y Bengio AAAI 1 (2), 3, 2008 | 285 | 2008 |
Christian SzegedyGoogle ResearchZweryfikowany adres z google.com
