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How Generative Adversarial Networks Promote the Development of Intelligent Transportation Systems: A Survey 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 9, 页码: 1781-1796
作者:  Hongyi Lin;  Yang Liu;  Shen Li;  Xiaobo Qu
Adobe PDF(1497Kb)  |  收藏  |  浏览/下载：164/95  |  提交时间：2023/08/10
Autonomous driving  generative adversarial network (GAN)  intelligent transportation system (ITS)  traffic anomaly inspection  traffic flow  
Deep Domain-Adversarial Anomaly Detection With One-Class Transfer Learning 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 2, 页码: 524-546
作者:  Wentao Mao;  Gangsheng Wang;  Linlin Kou;  Xihui Liang
Adobe PDF(25706Kb)  |  收藏  |  浏览/下载：679/43  |  提交时间：2023/01/16
Anomaly detection  domain adaptation  domain-adversarial training  one-class classification  transfer learning  
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：189/56  |  提交时间：2021/03/11
Collision avoidance  intelligent vehicles  inter-vehicle communication  simulation  testing  trajectory planning  
A Survey of the Research Status of Pedestrian Dead Reckoning Systems Based on Inertial Sensors 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 1, 页码: 65-83
作者:  Yuan Wu;  Hai-Bing Zhu;  Qing-Xiu Du;  Shu-Ming Tang
浏览  |  Adobe PDF(1248Kb)  |  收藏  |  浏览/下载：268/81  |  提交时间：2021/02/22
Inertial measurement unit (IMU)  pedestrian dead-reckoning  indoor navigation  technical route  general framework.  
Generalized Multiscale RBF Networks and the DCT for Breast Cancer Detection 期刊论文
International Journal of Automation and Computing, 2020, 卷号: 17, 期号: 1, 页码: 55-70
作者:  Carlos Beltran-Perez;  Hua-Liang Wei;  Adrian Rubio-Solis
Adobe PDF(1710Kb)  |  收藏  |  浏览/下载：157/56  |  提交时间：2021/02/22
Nonlinear system identification  image processing  discrete cosine transform  radial basis functions  computer-aided diagnosis  neural networks.