| Mobilenets: Efficient convolutional neural networks for mobile vision applications AG Howard, M Zhu, B Chen, D Kalenichenko, W Wang, T Weyand, ... arXiv preprint arXiv:1704.04861, 2017 | 18003 | 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 | 3878 | 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 | 2483 | 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 | 2201 | 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 | 1400 | 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 | 515 | 2018 |
| 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 | 322 | 2018 |
| Inductive principles for restricted Boltzmann machine learning B Marlin, K Swersky, B Chen, N Freitas Proceedings of the thirteenth international conference on artificial …, 2010 | 197 | 2010 |
| 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 | 106 | 2020 |
| Joint Optimization and Variable Selection of High-dimensional Gaussian Processes B Chen, R Castro, A Krause ICML, 2012 | 99 | 2012 |
| 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 | 93 | 2021 |
| 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 | 92 | 2019 |
| 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 | 86 | 2010 |
| Deep learning of invariant spatio-temporal features from video B Chen, de Freitas, Nando NIPS Deep Learning and Unsupervised Feature Learning Workshop, 2010 | 79 | 2010 |
| 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 | 59 | 2020 |
| Mobilenets: efficient convolutional neural networks for mobile vision applications. arXiv: 170404861 AG Howard, M Zhu, B Chen, D Kalenichenko, W Wang, T Weyand, ... URL http://arxiv. org/abs/1704.04861, 2017 | 52 | 2017 |
| 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 | 50 | 2019 |
| The hierarchical beta process for convolutional factor analysis and deep learning B Chen, G Polatkan, G Sapiro, L Carin, DB Dunson Proceedings of the 28th International Conference on Machine Learning (ICML …, 2011 | 49 | 2011 |
| Mnasfpn: Learning latency-aware pyramid architecture for object detection on mobile devices B Chen, G Ghiasi, H Liu, TY Lin, D Kalenichenko, H Adam, QV Le Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 45 | 2020 |
| Efficient convolutional neural networks and techniques to reduce associated computational costs AG Howard, B Chen, D Kalenichenko, TC Weyand, M Zhu, M Andreetto, ... US Patent 11,157,814, 2021 | 30 | 2021 |
Andrew HowardGoogle ResearchPotvrđena adresa e-pošte na google.com
