| Edge computing for autonomous driving: Opportunities and challenges S Liu, L Liu, J Tang, B Yu, Y Wang, W Shi Proceedings of the IEEE 107 (8), 1697-1716, 2019 | 576 | 2019 |
| Creating autonomous vehicle systems S Liu, L Li, J Tang, S Wu, JL Gaudiot Morgan & Claypool, 2018 | 227 | 2018 |
| Computer architectures for autonomous driving S Liu, J Tang, Z Zhang, JL Gaudiot Computer 50 (8), 18-25, 2017 | 201 | 2017 |
| Enabling deep learning on IoT devices J Tang, D Sun, S Liu, JL Gaudiot Computer 50 (10), 92-96, 2017 | 184 | 2017 |
| A survey of fpga-based robotic computing Z Wan, B Yu, TY Li, J Tang, Y Zhu, Y Wang, A Raychowdhury, S Liu IEEE Circuits and Systems Magazine 21 (2), 48-74, 2021 | 97 | 2021 |
| Building the computing system for autonomous micromobility vehicles: Design constraints and architectural optimizations B Yu, W Hu, L Xu, J Tang, S Liu, Y Zhu 2020 53rd Annual IEEE/ACM International Symposium on Microarchitecture …, 2020 | 79 | 2020 |
| LoPECS: A low-power edge computing system for real-time autonomous driving services J Tang, S Liu, L Liu, B Yu, W Shi IEEE Access 8, 30467-30479, 2020 | 61 | 2020 |
| A unified cloud platform for autonomous driving S Liu, J Tang, C Wang, Q Wang, JL Gaudiot Computer 50 (12), 42-49, 2017 | 59 | 2017 |
| Caad: Computer architecture for autonomous driving S Liu, J Tang, Z Zhang, JL Gaudiot arXiv preprint arXiv:1702.01894, 2017 | 44 | 2017 |
| A container based edge offloading framework for autonomous driving J Tang, R Yu, S Liu, JL Gaudiot ieee Access 8, 33713-33726, 2020 | 39 | 2020 |
| Prefetching in embedded mobile systems can be energy-efficient J Tang, S Liu, Z Gu, C Liu, JL Gaudiot IEEE Computer Architecture Letters 10 (1), 8-11, 2011 | 39 | 2011 |
| Autonomous last-mile delivery vehicles in complex traffic environments B Li, S Liu, J Tang, JL Gaudiot, L Zhang, Q Kong Computer 53 (11), 26-35, 2020 | 37 | 2020 |
| Acceleration of xml parsing through prefetching J Tang, S Liu, C Liu, Z Gu, JL Gaudiot IEEE Transactions on computers 62 (8), 1616-1628, 2012 | 34 | 2012 |
| Eudoxus: Characterizing and accelerating localization in autonomous machines industry track paper Y Gan, Y Bo, B Tian, L Xu, W Hu, S Liu, Q Liu, Y Zhang, J Tang, Y Zhu 2021 IEEE International Symposium on High-Performance Computer Architecture …, 2021 | 33 | 2021 |
| Towards fully intelligent transportation through infrastructure-vehicle cooperative autonomous driving: Challenges and opportunities S Liu, B Yu, J Tang, Q Zhu 2021 58th ACM/IEEE Design Automation Conference (DAC), 1323-1326, 2021 | 31 | 2021 |
| Implementing a cloud platform for autonomous driving S Liu, J Tang, C Wang, Q Wang, JL Gaudiot arXiv preprint arXiv:1704.02696, 2017 | 31 | 2017 |
| Archytas: A framework for synthesizing and dynamically optimizing accelerators for robotic localization W Liu, B Yu, Y Gan, Q Liu, J Tang, S Liu, Y Zhu MICRO-54: 54th Annual IEEE/ACM International Symposium on Microarchitecture …, 2021 | 28 | 2021 |
| An edge streaming data processing framework for autonomous driving H Zhao, LB Yao, ZX Zeng, DH Li, JL Xie, WL Zhu, J Tang Connection Science 33 (2), 173-200, 2021 | 28 | 2021 |
| Achieving middleware execution efficiency: hardware-assisted garbage collection operations J Tang, S Liu, Z Gu, XF Li, JL Gaudiot The Journal of Supercomputing 59, 1101-1119, 2012 | 28 | 2012 |
| Communication challenges in infrastructure-vehicle cooperative autonomous driving: A field deployment perspective S Liu, B Yu, J Tang, Y Zhu, X Liu IEEE Wireless Communications 29 (4), 126-131, 2022 | 24 | 2022 |
