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CASIA OpenIR
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Parallel Learning: Overview and Perspective for Computational Learning Across Syn2Real and Sim2Real 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 3, 页码: 603-631
作者:  Qinghai Miao;  Yisheng Lv;  Min Huang;  Xiao Wang;  Fei-Yue Wang
Adobe PDF(11937Kb)  |  收藏  |  浏览/下载：931/149  |  提交时间：2023/03/02
Machine learning  parallel learning  parallel systems  sim-to-real  syn-to-real  virtual-to-real  
A Semi-supervised End-to-end Framework for Transportation Mode Detection by Using GPS-enabled Sensing Devices 期刊论文
IEEE Internet of Things Journal, 2022, 卷号: 9, 期号: 10, 页码: 7842-7852
作者:  Zhishuai Li;  Gang Xiong;  Zebing Wei;  YIsheng Lv;  Noreen Anwar;  Fei-Yue Wang
Adobe PDF(2754Kb)  |  收藏  |  浏览/下载：233/72  |  提交时间：2022/04/08
Transportation mode detection , Semi-supervised learning, Human mobility , GPS trajectory.  
FII-CenterNet: An Anchor-Free Detector With Foreground Attention for Traffic Object Detection 期刊论文
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2021, 卷号: 70, 期号: 1, 页码: 121-132
作者:  Fan, Siqi;  Zhu, Fenghua;  Chen, Shichao;  Zhang, Hui;  Tian, Bin;  Lv, Yisheng;  Wang, Fei-Yue
Adobe PDF(7159Kb)  |  收藏  |  浏览/下载：268/39  |  提交时间：2021/03/29
Object detection  Anchor-free detector  Foreground region proposal  
Acting As A Decision Maker: Traffic-Condition-Aware Ensemble Learning for Traffic Flow Prediction 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2020, 期号: Accepted, 页码: Accepted
作者:  Yuanyuan Chen;  Hongyu Chen;  Peijun Ye;  Yisheng Lv;  Fei-Yue Wang
浏览  |  Adobe PDF(2382Kb)  |  收藏  |  浏览/下载：298/62  |  提交时间：2020/10/16
Traffic Flow Prediction  Ensemble Learning  Deep Learning  
On Iterative Proportional Updating: Limitations and Improvements for General Population Synthesis 期刊论文
IEEE Transactions on Cybernetics, 2022, 卷号: 52, 期号: 3, 页码: 1726-1735
作者:  Peijun Ye;  Bin Tian;  Yisheng Lv;  Qijie Li;  Fei-Yue Wang
Adobe PDF(1066Kb)  |  收藏  |  浏览/下载：244/51  |  提交时间：2020/10/15
Agent-based simulation, bilevel optimization, iterative proportional updating (IPU), population synthesis