| Multi-agent deep reinforcement learning for large-scale traffic signal control T Chu, J Wang, L Codecà, Z Li IEEE transactions on intelligent transportation systems 21 (3), 1086-1095, 2019 | 847 | 2019 |
| Deep learning-based apple detection using a suppression mask R-CNN P Chu, Z Li, K Lammers, R Lu, X Liu Pattern Recognition Letters 147, 206-211, 2021 | 126 | 2021 |
| Robust platoon control in mixed traffic flow based on tube model predictive control S Feng, Z Song, Z Li, Y Zhang, L Li IEEE Transactions on Intelligent Vehicles 6 (4), 711-722, 2021 | 114 | 2021 |
| YOLOWeeds: A novel benchmark of YOLO object detectors for multi-class weed detection in cotton production systems F Dang, D Chen, Y Lu, Z Li Computers and Electronics in Agriculture 205, 107655, 2023 | 110 | 2023 |
| Deep multi-agent reinforcement learning for highway on-ramp merging in mixed traffic D Chen, MR Hajidavalloo, Z Li, K Chen, Y Wang, L Jiang, Y Wang IEEE Transactions on Intelligent Transportation Systems 24 (11), 11623-11638, 2023 | 109 | 2023 |
| Distributed state estimation of sensor-network systems subject to Markovian channel switching with application to a chemical process X Yin, Z Li, L Zhang, M Han IEEE Transactions on Systems, Man, and Cybernetics: Systems 48 (6), 864-874, 2016 | 101 | 2016 |
| Performance evaluation of deep transfer learning on multi-class identification of common weed species in cotton production systems D Chen, Y Lu, Z Li, S Young Computers and Electronics in Agriculture 198, 107091, 2022 | 94 | 2022 |
| System design and control of an apple harvesting robot K Zhang, K Lammers, P Chu, Z Li, R Lu Mechatronics 79, 102644, 2021 | 92 | 2021 |
| Robust control of networked systems with variable communication capabilities and application to a semi-active suspension system X Yin, L Zhang, Y Zhu, C Wang, Z Li IEEE/ASME Transactions on Mechatronics 21 (4), 2097-2107, 2016 | 89 | 2016 |
| Visual-manual distraction detection using driving performance indicators with naturalistic driving data Z Li, S Bao, IV Kolmanovsky, X Yin IEEE Transactions on Intelligent Transportation Systems 19 (8), 2528-2535, 2017 | 87 | 2017 |
| Road disturbance estimation and cloud-aided comfort-based route planning Z Li, IV Kolmanovsky, EM Atkins, J Lu, DP Filev, Y Bai IEEE transactions on cybernetics 47 (11), 3879-3891, 2016 | 80 | 2016 |
| Road risk modeling and cloud-aided safety-based route planning Z Li, I Kolmanovsky, E Atkins, J Lu, DP Filev, J Michelini IEEE transactions on cybernetics 46 (11), 2473-2483, 2015 | 80 | 2015 |
| Infinite-step opacity and K-step opacity of stochastic discrete-event systems X Yin, Z Li, W Wang, S Li Automatica 99, 266-274, 2019 | 76 | 2019 |
| Autonomous driving using safe reinforcement learning by incorporating a regret-based human lane-changing decision model D Chen, L Jiang, Y Wang, Z Li 2020 American Control Conference (ACC), 4355-4361, 2020 | 74 | 2020 |
| Powernet: Multi-agent deep reinforcement learning for scalable powergrid control D Chen, K Chen, Z Li, T Chu, R Yao, F Qiu, K Lin IEEE Transactions on Power Systems 37 (2), 1007-1017, 2021 | 73 | 2021 |
| Multi-agent reinforcement learning for cooperative lane changing of connected and autonomous vehicles in mixed traffic W Zhou, D Chen, J Yan, Z Li, H Yin, W Ge Autonomous Intelligent Systems 2 (1), 5, 2022 | 70 | 2022 |
| Decentralized fault prognosis of discrete event systems with guaranteed performance bound X Yin, Z Li Automatica 69, 375-379, 2016 | 60 | 2016 |
| Safe reinforcement learning: Learning with supervision using a constraint-admissible set Z Li, U Kalabić, T Chu 2018 Annual American Control Conference (ACC), 6390-6395, 2018 | 58 | 2018 |
| Reliable decentralized fault prognosis of discrete-event systems X Yin, Z Li IEEE Transactions on Systems, Man, and Cybernetics: Systems 46 (11), 1598-1603, 2015 | 57 | 2015 |
| Federated learning’s blessing: Fedavg has linear speedup Z Qu, K Lin, Z Li, J Zhou ICLR 2021-Workshop on Distributed and Private Machine Learning (DPML), 2021 | 54 | 2021 |
