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CASIA OpenIR
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STGSA: A Novel Spatial-Temporal Graph Synchronous Aggregation Model for Traffic Prediction 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 1, 页码: 226-238
作者:  Zebing Wei;  Hongxia Zhao;  Zhishuai Li;  Xiaojie Bu;  Yuanyuan Chen;  Xiqiao Zhang;  Yisheng Lv;  Fei-Yue Wang
Adobe PDF(7068Kb)  |  收藏  |  浏览/下载：244/62  |  提交时间：2023/01/03
Deep learning  graph neural network (GNN)  multi-stream  spatial-temporal feature extraction  temporal graph  traffic prediction  
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：800/144  |  提交时间：2023/03/02
Machine learning  parallel learning  parallel systems  sim-to-real  syn-to-real  virtual-to-real  
Pavement Cracks Coupled With Shadows: A New Shadow-Crack Dataset and A Shadow-Removal-Oriented Crack Detection Approach 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 7, 页码: 1593-1607
作者:  Lili Fan;  Shen Li;  Ying Li;  Bai Li;  Dongpu Cao;  Fei-Yue Wang
Adobe PDF(23502Kb)  |  收藏  |  浏览/下载：87/13  |  提交时间：2023/06/14
Automatic pavement crack detection  data augmentation compensation  deep learning  residual feature augmentation  shadow removal  shadow-crack dataset  
Parallel Radars: From Digital Twins to Digital Intelligence for Smart Radar Systems 期刊论文
SENSORS, 2022, 卷号: 22, 期号: 24, 页码: 16
作者:  Liu, Yuhang;  Shen, Yu;  Fan, Lili;  Tian, Yonglin;  Ai, Yunfeng;  Tian, Bin;  Liu, Zhongmin;  Wang, Fei-Yue
收藏  |  浏览/下载：180/0  |  提交时间：2023/02/22
parallel radars  ACP method  cyber-physical-social systems (CPSS)  federated radars  
Meta-learning meets the Internet of Things: Graph prototypical models for sensor-based human activity recognition 期刊论文
INFORMATION FUSION, 2022, 卷号: 80, 页码: 1-22
作者:  Zheng, Wenbo;  Yan, Lan;  Gou, Chao;  Wang, Fei-Yue
收藏  |  浏览/下载：239/0  |  提交时间：2022/01/27
Meta-learning  Internet of Things  Graph model  Attention mechanisms  
AdapGL: An adaptive graph learning algorithm for traffic prediction based on spatiotemporal neural networks 期刊论文
Transportation Research Part C, 2022, 期号: 99, 页码: 1-1
作者:  Wei Zhang;  Fenghua Zhu;  Yisheng Lv;  Chang Tan;  Wen Liu;  Xin Zhang;  Fei-Yue Wang
Adobe PDF(2619Kb)  |  收藏  |  浏览/下载：355/116  |  提交时间：2022/04/08
Adaptive graph learning, Traffic prediction, Graph convolutional network, Expectation maximization, Deep learning  
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：206/61  |  提交时间：2022/04/08
Transportation mode detection , Semi-supervised learning, Human mobility , GPS trajectory.  
Simulation and Field Testing of Multiple Vehicles Collision Avoidance Algorithms 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2020, 卷号: 7, 期号: 4, 页码: 1045-1063
作者:  Chaoyue Zu;  Chao Yang;  Jian Wang;  Wenbin Gao;  Dongpu Cao;  Fei-Yue Wang
浏览  |  Adobe PDF(40115Kb)  |  收藏  |  浏览/下载：170/56  |  提交时间：2021/03/11
Collision avoidance  intelligent vehicles  inter-vehicle communication  simulation  testing  trajectory planning  
Proximity Based Automatic Data Annotation for Autonomous Driving 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2020, 卷号: 7, 期号: 2, 页码: 395-404
作者:  Chen Sun;  Jean M. Uwabeza Vianney;  Ying Li;  Long Chen;  Li Li;  Fei-Yue Wang;  Amir Khajepour;  Dongpu Cao
浏览  |  Adobe PDF(12990Kb)  |  收藏  |  浏览/下载：173/41  |  提交时间：2021/03/11
Affordance learning  autonomous vehicles  data synchronization  scene understanding  
Pattern Sensitive Prediction of Traffic Flow Based on Generative Adversarial Framework 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2019, 卷号: 20, 期号: 6, 页码: 2395-2400
作者:  Lin, Yilun;  Dai, Xingyuan;  Li, Li;  Wang, Fei-Yue
浏览  |  Adobe PDF(623Kb)  |  收藏  |  浏览/下载：353/151  |  提交时间：2019/05/07
Traflic flow prediction  deep learning  generative adversarial network