| 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 | 60964 | 2015 |
| Batch normalization: Accelerating deep network training by reducing internal covariate shift S Ioffe, C Szegedy International conference on machine learning, 448-456, 2015 | 56369 | 2015 |
| Ssd: Single shot multibox detector W Liu, D Anguelov, D Erhan, C Szegedy, S Reed, CY Fu, AC Berg Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016 | 39361 | 2016 |
| Rethinking the inception architecture for computer vision C Szegedy, V Vanhoucke, S Ioffe, J Shlens, Z Wojna Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 34112 | 2016 |
| Explaining and harnessing adversarial examples IJ Goodfellow, J Shlens, C Szegedy arXiv preprint arXiv:1412.6572, 2014 | 21218 | 2014 |
| Inception-v4, inception-resnet and the impact of residual connections on learning C Szegedy, S Ioffe, V Vanhoucke, A Alemi Proceedings of the AAAI conference on artificial intelligence 31 (1), 2017 | 17164 | 2017 |
| Intriguing properties of neural networks C Szegedy, W Zaremba, I Sutskever, J Bruna, D Erhan, I Goodfellow, ... arXiv preprint arXiv:1312.6199, 2013 | 16856 | 2013 |
| Deeppose: Human pose estimation via deep neural networks A Toshev, C Szegedy Proceedings of the IEEE conference on computer vision and pattern …, 2014 | 3768 | 2014 |
| Deep neural networks for object detection C Szegedy, A Toshev, D Erhan Advances in neural information processing systems 26, 2013 | 2024 | 2013 |
| European conference on computer vision W Liu, D Anguelov, D Erhan, C Szegedy, S Reed, CY Fu, AC Berg Face detection with end-to-end integration of a convnet and a 3d model, 2016 | 1765 | 2016 |
| 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 | 1572 | 2014 |
| Batch normalization: Accelerating deep network training by reducing internal covariate shift. arXiv 2015 S Ioffe, C Szegedy arXiv preprint arXiv:1502.03167, 2015 | 1243 | 2015 |
| 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 | 1154 | 2014 |
| Scalable, high-quality object detection C Szegedy, S Reed, D Erhan, D Anguelov, S Ioffe arXiv preprint arXiv:1412.1441, 2014 | 554 | 2014 |
| Going deeper with convolutions. arXiv 2014 C Szegedy, W Liu, Y Jia, P Sermanet, S Reed, D Anguelov, D Erhan, ... arXiv preprint arXiv:1409.4842 1409, 2015 | 505 | 2015 |
| Inception-v4 C Szegedy, S Ioffe, V Vanhoucke, A Alemi Inception-ResNet and the impact of residual connections on learning 1602, 2016 | 370 | 2016 |
| Intriguing properties of neural networks. arXiv 2013 C Szegedy, W Zaremba, I Sutskever, J Bruna, D Erhan, I Goodfellow, ... arXiv preprint arXiv:1312.6199 103, 2013 | 357 | 2013 |
| Deepmath-deep sequence models for premise selection G Irving, C Szegedy, AA Alemi, N Eén, F Chollet, J Urban Advances in neural information processing systems 29, 2016 | 272* | 2016 |
| Rethinking the inception architecture for computer vision. 2015 C Szegedy, V Vanhoucke, S Ioffe, J Shlens, Z Wojna arXiv preprint arXiv:1512.00567, 2015 | 258 | 2015 |
| Intriguing properties of neural networks J Bruna, C Szegedy, I Sutskever, I Goodfellow, W Zaremba, R Fergus, ... | 218 | 2013 |
Dumitru ErhanDirector of Research @ Google DeepMindBestätigte E-Mail-Adresse bei google.com
