| Mobilenets: Efficient convolutional neural networks for mobile vision applications AG Howard arXiv preprint arXiv:1704.04861, 2017 | 27057 | 2017 |
| 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 | 8563 | 2019 |
| 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 | 3673 | 2019 |
| Quantization and training of neural networks for efficient integer-arithmetic-only inference B Jacob, S Kligys, B Chen, M Zhu, M Tang, A Howard, H Adam, ... Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 3566 | 2018 |
| Learning Fine-grained Image Similarity with Deep Ranking J Wang, Y Song, T Leung, C Rosenberg, J Wang, J Philbin, B Chen, Y Wu CVPR, 2014 | 1663 | 2014 |
| Netadapt: Platform-aware neural network adaptation for mobile applications TJ Yang, A Howard, B Chen, X Zhang, A Go, M Sandler, V Sze, H Adam Proceedings of the European conference on computer vision (ECCV), 285-300, 2018 | 712 | 2018 |
| MobileNets: efficient convolutional neural networks for mobile vision applications (2017) AG Howard, M Zhu, B Chen, D Kalenichenko, W Wang, T Weyand, ... arXiv preprint arXiv:1704.04861 126, 2017 | 594 | 2017 |
| Morphnet: Fast & simple resource-constrained structure learning of deep networks A Gordon, E Eban, O Nachum, B Chen, H Wu, TJ Yang, E Choi Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 412 | 2018 |
| Mobilenets: Efficient convolutional neural networks for mobile vision applications. arXiv preprint (2017) AG Howard, M Zhu, B Chen, D Kalenichenko, W Wang, T Weyand, ... arXiv preprint arXiv:1704.04861, 2017 | 215 | 2017 |
| Inductive principles for restricted Boltzmann machine learning B Marlin, K Swersky, B Chen, N Freitas Proceedings of the thirteenth international conference on artificial …, 2010 | 209 | 2010 |
| Satellite pose estimation with deep landmark regression and nonlinear pose refinement B Chen, J Cao, A Parra, TJ Chin Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 178 | 2019 |
| 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 | 161 | 2021 |
| Can weight sharing outperform random architecture search? an investigation with tunas G Bender, H Liu, B Chen, G Chu, S Cheng, PJ Kindermans, QV Le Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 155 | 2020 |
| End-to-end learnable geometric vision by backpropagating pnp optimization B Chen, A Parra, J Cao, N Li, TJ Chin Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 114 | 2020 |
| Joint Optimization and Variable Selection of High-dimensional Gaussian Processes B Chen, R Castro, A Krause ICML, 2012 | 110 | 2012 |
| Low-power computer vision: Status, challenges, and opportunities S Alyamkin, M Ardi, AC Berg, A Brighton, B Chen, Y Chen, HP Cheng, ... IEEE Journal on Emerging and Selected Topics in Circuits and Systems 9 (2 …, 2019 | 96 | 2019 |
| Mobilenets: E cient convolutional neural networks for mobile vision applications AG Howard, M Zhu, B Chen, D Kalenichenko, W Wang, T Weyand, ... arXiv preprint arXiv:1704.04861 2, 2017 | 91 | 2017 |
| A tutorial on stochastic approximation algorithms for training restricted Boltzmann machines and deep belief nets K Swersky, B Chen, B Marlin, N de Freitas ITA Workshop, 2010 | 89 | 2010 |
| Deep learning of invariant spatio-temporal features from video B Chen, de Freitas, Nando NIPS Deep Learning and Unsupervised Feature Learning Workshop, 2010 | 82 | 2010 |
| Searching for mobilenetv3. arXiv 2019 A Howard, M Sandler, G Chu, LC Chen, B Chen, M Tan, W Wang, Y Zhu, ... arXiv preprint arXiv:1905.02244, 1905 | 81 | 1905 |
Andrew HowardGoogle ResearchVerified email at google.com
