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CASIA OpenIR
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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：93/13  |  提交时间：2023/06/14
Automatic pavement crack detection  data augmentation compensation  deep learning  residual feature augmentation  shadow removal  shadow-crack dataset  
DAO to Hanoi via DeSci: AI Paradigm Shift from AlphaGo to ChatGPT 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 4, 页码: 877-897
作者:  Miao, Qinghai (proxy) (contact);  Zheng, Wenbo;  吕, 宜生;  Huang, Min;  Ding, Wenwen;  Wang, Fei-Yue
Adobe PDF(4968Kb)  |  收藏  |  浏览/下载：238/67  |  提交时间：2023/03/22
ChatGPT, decentralized science (DeSci)  decentralized autonomous organization (DAO)  machine learning  paradigm shift  
The Development of AgriVerse: Past, Present, and Future 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2023, 页码: 10
作者:  Kang, Mengzhen;  Wang, Xiujuan;  Wang, Haoyu;  Hua, Jing;  de Reffye, Philippe;  Wang, Fei-Yue
Adobe PDF(4290Kb)  |  收藏  |  浏览/下载：281/73  |  提交时间：2023/02/22
Computational modeling  Biological systems  Biomass  Biological system modeling  Production  Plants (biology)  Metaverse  Agricultural metaverse (AgriVerse)  agriculture cyber-physical-social system (CPSS)  artificial systems  computational experiments  and parallel execution (ACP)  decentralized science (DeSci)  knowledge-and-data driven modeling  parallel agriculture  plant model  
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：255/65  |  提交时间：2023/01/03
Deep learning  graph neural network (GNN)  multi-stream  spatial-temporal feature extraction  temporal graph  traffic prediction