| Efficient Processing of Deep Neural Networks: A Tutorial and Survey V Sze, YH Chen, TJ Yang, J Emer Proceedings of the IEEE 105 (12), 2295-2329, 2017 | 4704 | 2017 |
| Eyeriss: An Energy-Efficient Reconfigurable Accelerator for Deep Convolutional Neural Networks YH Chen, T Krishna, J Emer, V Sze 2016 IEEE International Solid-State Circuits Conference (ISSCC), 262-263, 2016 | 4104 | 2016 |
| Eyeriss: A Spatial Architecture for Energy-Efficient Dataflow for Convolutional Neural Networks YH Chen, J Emer, V Sze International Symposium on Computer Architecture (ISCA), 2016 | 2041 | 2016 |
| Eyeriss v2: A Flexible Accelerator for Emerging Deep Neural Networks on Mobile Devices YH Chen, TJ Yang, J Emer, V Sze IEEE Journal on Emerging and Selected Topics in Circuits and Systems 9 (2 …, 2019 | 1273* | 2019 |
| Designing Energy-Efficient Convolutional Neural Networks Using Energy-Aware Pruning TJ Yang, YH Chen, V Sze Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017 | 1088 | 2017 |
| High Efficiency Video Coding (HEVC): Algorithms and Architectures V Sze, M Budagavi, GJ Sullivan Springer, 2014 | 884* | 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 European Conference on Computer Vision (ECCV), 2018 | 739 | 2018 |
| Hardware for Machine Learning: Challenges and Opportunities V Sze, YH Chen, J Emer, A Suleiman, Z Zhang Custom Integrated Circuits Conference (CICC), 2017 IEEE, 1-8, 2017 | 496 | 2017 |
| FastDepth: Fast Monocular Depth Estimation on Embedded Systems D Wofk, F Ma, TJ Yang, S Karaman, V Sze IEEE International Conference on Robotics and Automation (ICRA), 2019 | 390 | 2019 |
| High Throughput CABAC Entropy Coding in HEVC V Sze, M Budagavi IEEE Transactions on Circuits and Systems for Video Technology 22 (12), 1778 …, 2012 | 354 | 2012 |
| Efficient Processing of Deep Neural Networks V Sze, YH Chen, TJ Yang, JS Emer Morgan & Claypool Publishers, 2020 | 327* | 2020 |
| A Method to Estimate the Energy Consumption of Deep Neural Networks TJ Yang, YH Chen, J Emer, V Sze Asilomar Conference on Signals, Systems and Computers, 2017 | 285 | 2017 |
| Using Dataflow to Optimize Energy Efficiency of Deep Neural Network Accelerators YH Chen, J Emer, V Sze IEEE Micro’s Top Picks from the Computer Architecture Conferences 37 (3), 2017 | 279 | 2017 |
| Accelergy: An Architecture-Level Energy Estimation Methodology for Accelerator Designs YN Wu, J Emer, V Sze International Conference on Computer-Aided Design (ICCAD), 2019 | 272 | 2019 |
| Core Transform Design in the High Efficiency Video Coding (HEVC) Standard M Budagavi, A Fuldseth, G Bjontegaard, V Sze, M Sadafale IEEE Journal of Selected Topics in Signal Processing 7 (6), 1029-1041, 2013 | 243 | 2013 |
| Parallel motion estimation in video coding US Patent 20,120,257,678, 2015 | 240* | 2015 |
| DeeperLab: Single-Shot Image Parser TJ Yang, MD Collins, Y Zhu, JJ Hwang, T Liu, X Zhang, V Sze, ... arXiv preprint arXiv:1902.05093, 2019 | 223 | 2019 |
| Navion: A Fully Integrated Energy-Efficient Visual-Inertial Odometry Accelerator for Autonomous Navigation of Nano Drones A Suleiman, Z Zhang, L Carlone, S Karaman, V Sze IEEE Symposium on VLSI Circuits (VLSI-Circuits), 2018 | 212* | 2018 |
| Hardware architectures for deep neural networks J Emer, V Sze, YH Chen, TJ Yang CICS/MTL Tutorial, 2017 | 184* | 2017 |
| Technologies for Ultradynamic Voltage Scaling AP Chandrakasan, DC Daly, DF Finchelstein, J Kwong, YK Ramadass, ... Proceedings of the IEEE 98 (2), 191-214, 2010 | 143 | 2010 |
Joel EmerProfessor of the Practice, MIT - Sr. Distinguished Research Scientist, Nvidia確認したメール アドレス: csail.mit.edu