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ParaUDA: Invariant Feature Learning With Auxiliary Synthetic Samples for Unsupervised Domain Adaptation 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 卷号: 23, 期号: 11, 页码: 20217-20229
作者:  Zhang, Wenwen;  Wang, Jiangong;  Wang, Yutong;  Wang, Fei-Yue
收藏  |  浏览/下载:77/0  |  提交时间:2023/03/20
Adaptation models  Representation learning  Feature extraction  Task analysis  Semantics  Generative adversarial networks  Object detection  Object detection  unsupervised domain adaptation  distribution alignment  domain-invariant representation  
Trip Purposes Mining From Mobile Signaling Data 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2021, 卷号: 99, 期号: 99, 页码: 13
作者:  Li, Zhishuai;  Xiong, Gang;  Wei, Zebing;  Zhang, Yu;  Zheng, Meng;  Liu, Xiaoli;  Tarkoma, Sasu;  Huang, Min;  Lv, Yisheng;  Wu, Chuheng
Adobe PDF(3962Kb)  |  收藏  |  浏览/下载:378/71  |  提交时间:2022/01/27
Cellular networks  Trajectory  Semantics  Unsupervised learning  Supervised learning  Resource management  Public transportation  Trip purpose inference  cellular network data  latent Dirichlet allocation  travel behavior  big data  
Traffic Flow Imputation Using Parallel Data and Generative Adversarial Networks 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2020, 卷号: 21, 期号: 4, 页码: 1624-1630
作者:  Chen, Yuanyuan;  Lv, Yisheng;  Wang, Fei-Yue
浏览  |  Adobe PDF(2070Kb)  |  收藏  |  浏览/下载:363/65  |  提交时间:2020/06/02
Generators  Data models  Gallium nitride  Generative adversarial networks  Training  Loss measurement  Biological system modeling  Parallel data  generative adversarial networks  traffic flow imputation  data augmentation  deep learning