| Going deeper with convolutions C Szegedy, W Liu, Y Jia, P Sermanet, S Reed, D Anguelov, D Erhan, ... 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 1-9, 2015 | 56082 | 2015 |
| Rethinking the inception architecture for computer vision C Szegedy, V Vanhoucke, S Ioffe, J Shlens, Z Wojna 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2818 …, 2016 | 30346 | 2016 |
| Tensorflow: Large-scale machine learning on heterogeneous distributed systems M Abadi, A Agarwal, P Barham, E Brevdo, Z Chen, C Citro, GS Corrado, ... arXiv preprint arXiv:1603.04467, 2016 | 29455 | 2016 |
| 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 | 15750 | 2017 |
| Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups G Hinton, L Deng, D Yu, GE Dahl, A Mohamed, N Jaitly, A Senior, ... IEEE Signal processing magazine 29 (6), 82-97, 2012 | 13140 | 2012 |
| Scalable deep reinforcement learning for vision-based robotic manipulation D Kalashnikov, A Irpan, P Pastor, J Ibarz, A Herzog, E Jang, D Quillen, ... 2nd Conference on Robot Learning (CoRL), 651-673, 2018 | 1313* | 2018 |
| Improving the speed of neural networks on CPUs V Vanhoucke, A Senior, MZ Mao 2011 NIPS Deep Learning and Unsupervised Feature Learning Workshop, 2011 | 1022 | 2011 |
| System and method for enabling the use of captured images through recognition US Patent 20,060,251,339, 0 | 741* | |
| Sim-to-real: Learning agile locomotion for quadruped robots J Tan, T Zhang, E Coumans, A Iscen, Y Bai, D Hafner, S Bohez, ... Robotics: Science and Systems (RSS) XIV, 2018 | 740 | 2018 |
| On rectified linear units for speech processing MD Zeiler, M Ranzato, R Monga, M Mao, K Yang, QV Le, P Nguyen, ... 2013 IEEE International Conference on Acoustics, Speech and Signal …, 2013 | 712 | 2013 |
| Using simulation and domain adaptation to improve efficiency of deep robotic grasping K Bousmalis, A Irpan, P Wohlhart, Y Bai, M Kelcey, M Kalakrishnan, ... 2018 IEEE International Conference on Robotics and Automation (ICRA), 4243-4250, 2018 | 680 | 2018 |
| Do as I can, not as I say: Grounding language in robotic affordances M Ahn, A Brohan, N Brown, Y Chebotar, O Cortes, B David, C Finn, ... arXiv preprint arXiv:2204.01691, 2022 | 659* | 2022 |
| YouTube-BoundingBoxes: A large high-precision human-annotated data set for object detection in video E Real, J Shlens, S Mazzocchi, X Pan, V Vanhoucke IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 5296-5305, 2017 | 614 | 2017 |
| System and method for enabling search and retrieval from image files based on recognized information SB Gokturk, D Anguelov, V Vanhoucke, K Lee, D Vu, D Yang, M Shah, ... US Patent 7,809,722, 2010 | 522 | 2010 |
| System and method for providing objectified image renderings using recognition information from images SB Gokturk, D Anguelov, V Vanhoucke, K Lee, D Vu, D Yang, M Shah, ... US Patent 7,783,135, 2010 | 478* | 2010 |
| System and method for recognizing objects from images and identifying relevancy amongst images and information SB Gokturk, D Anguelov, V Vanhoucke, K Lee, D Vu, D Yang, M Shah, ... US Patent 7,809,192, 2010 | 468 | 2010 |
| System and method for enabling image recognition and searching of images SB Gokturk, B Sumengen, D Vu, N Dalal, D Yang, X Lin, A Khan, M Shah, ... US Patent 7,657,100, 2010 | 446 | 2010 |
| System and method for search portions of objects in images and features thereof SB Gokturk, B Sumengen, D Vu, N Dalal, D Yang, X Lin, A Khan, M Shah, ... US Patent 7,657,126, 2010 | 415* | 2010 |
| PaLM-E: An embodied multimodal language model D Driess, F Xia, MSM Sajjadi, C Lynch, A Chowdhery, B Ichter, A Wahid, ... arXiv preprint arXiv:2303.03378, 2023 | 388 | 2023 |
| System and method for enabling image recognition and searching of remote content on display US Patent 20,080,082,426, 0 | 377* | |
Dragomir AnguelovDistinguished Researcher, WaymoEmail verificata su cs.stanford.edu
