| 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 | 66714 | 2015 |
| Batch normalization: Accelerating deep network training by reducing internal covariate shift S Ioffe, C Szegedy International conference on machine learning, 448-456, 2015 | 61424 | 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 | 45156 | 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 | 38379 | 2016 |
| Explaining and harnessing adversarial examples IJ Goodfellow, J Shlens, C Szegedy arXiv preprint arXiv:1412.6572, 2014 | 24346 | 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 | 18988 | 2017 |
| Intriguing properties of neural networks C Szegedy, W Zaremba, I Sutskever, J Bruna, D Erhan, I Goodfellow, ... arXiv preprint arXiv:1312.6199, 2013 | 18954 | 2013 |
| Deeppose: Human pose estimation via deep neural networks A Toshev, C Szegedy Proceedings of the IEEE conference on computer vision and pattern …, 2014 | 4133 | 2014 |
| Deep neural networks for object detection C Szegedy, A Toshev, D Erhan Advances in neural information processing systems 26, 2013 | 2147 | 2013 |
| 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 | 1636 | 2014 |
| 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 | 1245 | 2014 |
| Leibe B, Matas J, Sebe N, Welling M, et al. SSD: single shot multibox detector W Liu, D Anguelov, D Erhan, C Szegedy, S Reed, CY Fu, AC Berg Computer Vision–ECCV 2016, 21-37, 2016 | 851 | 2016 |
| Scalable, high-quality object detection C Szegedy, S Reed, D Erhan, D Anguelov, S Ioffe arXiv preprint arXiv:1412.1441, 2014 | 565 | 2014 |
| 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 | 288* | 2016 |
| Memorizing transformers Y Wu, MN Rabe, DL Hutchins, C Szegedy arXiv preprint arXiv:2203.08913, 2022 | 280 | 2022 |
| Inception-v4, inception-resnet and the impact of residual connections on learning. arXiv 2016 C Szegedy, S Ioffe, V Vanhoucke, A Alemi arXiv preprint arXiv:1602.07261, 2023 | 274 | 2023 |
| Going deeper with convolutions (2014) C Szegedy, W Liu, Y Jia, P Sermanet, S Reed, D Anguelov, D Erhan, ... arXiv preprint arXiv:1409.4842 10, 2014 | 273 | 2014 |
| Deep network guided proof search S Loos, G Irving, C Szegedy, C Kaliszyk arXiv preprint arXiv:1701.06972, 2017 | 204 | 2017 |
| Holist: An environment for machine learning of higher order logic theorem proving K Bansal, S Loos, M Rabe, C Szegedy, S Wilcox International Conference on Machine Learning, 454-463, 2019 | 189 | 2019 |
| Proceedings of the 32nd International Conference on Machine Learning S Ioffe, C Szegedy, F Bach, D Blei Proc. Mach. Learn. Res. Vol. 37, 448, 2015 | 184 | 2015 |
Dumitru ErhanDirector of Research @ Google DeepMindVerified email at google.com
