| Efficientnet: Rethinking model scaling for convolutional neural networks M Tan, Q Le International conference on machine learning, 6105-6114, 2019 | 33526 | 2019 |
| Searching for mobilenetv3 A Howard, M Sandler, G Chu, LC Chen, B Chen, M Tan, W Wang, Y Zhu, ... Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 13340 | 2019 |
| Efficientdet: Scalable and efficient object detection M Tan, R Pang, QV Le Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 10870 | 2020 |
| Efficientnetv2: Smaller models and faster training M Tan, QV Le International Conference on Machine Learning, 2021 | 5506 | 2021 |
| Mnasnet: Platform-aware neural architecture search for mobile M Tan, B Chen, R Pang, V Vasudevan, M Sandler, A Howard, QV Le Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 4514 | 2019 |
| Rethinking model scaling for convolutional neural networks M Tan, QE Le Proceedings of the International conference on machine learning, Long Beach …, 2019 | 4015 | 2019 |
| Coatnet: Marrying convolution and attention for all data sizes Z Dai, H Liu, QV Le, M Tan Advances in neural information processing systems 34, 3965-3977, 2021 | 1950 | 2021 |
| Adversarial examples improve image recognition C Xie, M Tan, B Gong, J Wang, AL Yuille, QV Le Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 760 | 2020 |
| Nyströmformer: A nyström-based algorithm for approximating self-attention Y Xiong, Z Zeng, R Chakraborty, M Tan, G Fung, Y Li, V Singh Proceedings of the AAAI conference on artificial intelligence 35 (16), 14138 …, 2021 | 720 | 2021 |
| DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection Y Li, AW Yu, T Meng, B Caine, J Ngiam, D Peng, J Shen, B Wu, Y Lu, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 651 | 2022 |
| MixConv: Mixed Depthwise Convolutional Kernels M Tan, QV Le Proceedings of the 30th British Machine Vision Conference (BMVC), 2019 | 639 | 2019 |
| Bignas: Scaling up neural architecture search with big single-stage models J Yu, P Jin, H Liu, G Bender, PJ Kindermans, M Tan, T Huang, X Song, ... European Conference on Computer Vision, 702-717, 2020 | 392 | 2020 |
| Movinets: Mobile video networks for efficient video recognition D Kondratyuk, L Yuan, Y Li, L Zhang, M Tan, M Brown, B Gong Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 380 | 2021 |
| PolyLoss: A Polynomial Expansion Perspective of Classification Loss Functions Z Leng, M Tan, C Liu, ED Cubuk, J Shi, S Cheng, D Anguelov International Conference on Learning Representations, 2022 | 287 | 2022 |
| Spinenet: Learning scale-permuted backbone for recognition and localization X Du, TY Lin, P Jin, G Ghiasi, M Tan, Y Cui, QV Le, X Song Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 274 | 2020 |
| Combined scaling for zero-shot transfer learning H Pham, Z Dai, G Ghiasi, K Kawaguchi, H Liu, AW Yu, J Yu, YT Chen, ... Neurocomputing, 126658, 2023 | 237 | 2023 |
| Mobiledets: Searching for object detection architectures for mobile accelerators Y Xiong, H Liu, S Gupta, B Akin, G Bender, Y Wang, PJ Kindermans, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 225 | 2021 |
| Smooth adversarial training C Xie, M Tan, B Gong, A Yuille, QV Le arXiv preprint arXiv:2006.14536, 2020 | 220 | 2020 |
| SWFormer: Sparse Window Transformer for 3D Object Detection in Point Clouds P Sun, M Tan, W Wang, C Liu, F Xia, Z Leng, D Anguelov European Conference on Computer Vision (ECCV), 2022 | 196 | 2022 |
| Emma: End-to-end multimodal model for autonomous driving JJ Hwang, R Xu, H Lin, WC Hung, J Ji, K Choi, D Huang, T He, ... arXiv preprint arXiv:2410.23262, 2024 | 168 | 2024 |
Quoc V. LeResearch Scientist, GoogleVerified email at stanford.edu
