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CASIA OpenIR
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CGNN: A Compatibility-aware Graph Neural Network for Social Media Bot Detection 期刊论文
IEEE Transactions on Computational Social System, 2024, 页码: Early Access
作者:  Huang, Haitao;  Tian, Hu;  Zheng, Xiaolong;  Zhang, Xingwei;  Zeng, Dajun;  Wang, Feiyue
Adobe PDF(2267Kb)  |  收藏  |  浏览/下载：6/4  |  提交时间：2024/07/08
graph neural network  heterogeneous compatibility  social media bot detection  
The survey on multi-source data fusion in cyber-physical-social systems: Foundational infrastructure for industrial metaverses and industries 5.0 期刊论文
Information Fusion, 2024, 卷号: 107, 页码: 1-16
作者:  Xiao Wang;  Yutong Wang;  Jing Yang;  Xiaofeng Jia;  Lijun Li;  Weiping Ding;  Fei-Yue Wang
Adobe PDF(4446Kb)  |  收藏  |  浏览/下载：32/2  |  提交时间：2024/06/06
Multi-source data fusion  CPSS  Industrial metaverses  Parallel manufacturing  Social manufacturing  
What Does Sora Show: The Beginning of TAO to Imaginative Intelligence and Scenarios Engineering 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 4, 页码: 809-815
作者:  Fei-Yue Wang;  Qinghai Miao;  Lingxi Li;  Qinghua Ni;  Xuan Li;  Juanjuan Li;  Lili Fan;  Yonglin Tian;  Qing-Long Han
Adobe PDF(571Kb)  |  收藏  |  浏览/下载：59/13  |  提交时间：2024/03/18
ArtCap: A Dataset for Image Captioning of Fine Art Paintings 期刊论文
IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS, 2022, 页码: 12
作者:  Lu, Yue;  Guo, Chao;  Dai, Xingyuan;  Wang, Fei-Yue
Adobe PDF(5137Kb)  |  收藏  |  浏览/下载：273/49  |  提交时间：2023/02/22
Dataset construction  image captioning  painting captioning  
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：292/72  |  提交时间：2023/01/03
Deep learning  graph neural network (GNN)  multi-stream  spatial-temporal feature extraction  temporal graph  traffic prediction  
HMDRL: Hierarchical Mixed Deep Reinforcement Learning to Balance Vehicle Supply and Demand 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 卷号: 23, 期号: 11, 页码: 21861-21872
作者:  Xi, Jinhao;  Zhu, Fenghua;  Ye, Peijun;  Lv, Yisheng;  Tang, Haina;  Wang, Fei-Yue
Adobe PDF(3316Kb)  |  收藏  |  浏览/下载：303/39  |  提交时间：2022/09/19
deep reinforcement learning  online ride-hailing system  hierarchical repositioning framework  parallel coordination mechanism  mixed state  
ESTNet: Embedded Spatial-Temporal Network for Modeling Traffic Flow Dynamics 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 页码: 12
作者:  Luo, Guiyang;  Zhang, Hui;  Yuan, Quan;  Li, Jinglin;  Wang, Fei-Yue
收藏  |  浏览/下载：210/0  |  提交时间：2022/07/25
Roads  Correlation  Feature extraction  Sensors  Deep learning  Convolution  Sensor phenomena and characterization  Traffic forecasting  graph convolutional network  spatial-temporal networks  
Improving Road Detection Results Based on Ensemble Learning and Key Samples Focusing 会议论文
Proceedings of the IEEE International Conference on Intelligent Transportation Systems (ITSC), Rhodes, Greece; Online, 2020-9-20
作者:  Fan, Siqi;  Zhu, Fenghua;  Zhang, Hui;  Lv, Yisheng;  Wang, Xiao;  Xiong, Gang;  Wang, Feiyue
Adobe PDF(2270Kb)  |  收藏  |  浏览/下载：266/59  |  提交时间：2022/06/16
SegDQ: Segmentation assisted multi-object tracking with dynamic query-based transformers 期刊论文
NEUROCOMPUTING, 2022, 卷号: 481, 页码: 91-101
作者:  Liu, Yating;  Bai, Tianxiang;  Tian, Yonglin;  Wang, Yutong;  Wang, Jiangong;  Wang, Xiao;  Wang, Fei-Yue
Adobe PDF(2635Kb)  |  收藏  |  浏览/下载：330/47  |  提交时间：2022/06/06
Multi-object tracking  Transformer  Semantic task  Dynamic query  
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：411/135  |  提交时间：2022/04/08
Adaptive graph learning, Traffic prediction, Graph convolutional network, Expectation maximization, Deep learning