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Toward few-shot domain adaptation with perturbation-invariant representation and transferable prototypes 期刊论文
FRONTIERS OF COMPUTER SCIENCE, 2022, 卷号: 16, 期号: 3, 页码: 11
作者:  Fan, Junsong;  Wang, Yuxi;  Guan, He;  Song, Chunfeng;  Zhang, Zhaoxiang
Adobe PDF(4804Kb)  |  收藏  |  浏览/下载：268/46  |  提交时间：2022/06/10
domain adaptation  semantic segmentation  
An IVC-Based Nuclear Emergency Parallel Evacuation System 期刊论文
IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS, 2021, 卷号: 8, 期号: 4, 页码: 844-855
作者:  Tan, Ke;  Yang, Linyao;  Liu, Xin;  Xu, Yancai;  Lin, Jiazhen;  Wang, Xiao;  Wang, Fei-Yue
Adobe PDF(2418Kb)  |  收藏  |  浏览/下载：252/38  |  提交时间：2021/11/02
Computational modeling  Planning  Optimization  Roads  Mathematical model  Collaboration  Power generation  ACP  intelligent vehicle collaborative system  nuclear evacuation  optimization  parallel intelligence  
A Self-Supervised CNN for Particle Inspection on Optical Element 期刊论文
IEEE Transactions on Instrumentation and Measurement, 2021, 卷号: 70, 期号: 1, 页码: 1-12
作者:  Hou W(侯伟);  Tao X(陶显);  Xu D(徐德)
Adobe PDF(2721Kb)  |  收藏  |  浏览/下载：247/58  |  提交时间：2021/06/21
Inspection  Feature reuse  optical element  particle inspection  self-supervised learning  transfer learning  
Combining Prior Knowledge With CNN for Weak Scratch Inspection of Optical Components 期刊论文
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2021, 卷号: 70, 期号: 1, 页码: 11
作者:  Hou, Wei;  Tao, Xian;  Xu, De
Adobe PDF(6798Kb)  |  收藏  |  浏览/下载：368/129  |  提交时间：2021/03/08
Convolutional neural network (CNN)  direction-sensitive convolution (DSC)  local maximum index (LMI)  optical component  weak scratch inspection  
Prediction of Spatiotemporal Evolution of Urban Traffic Emissions Based on Taxi Trajectories 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 2, 页码: 219-232
作者:  Zhen-Yi Zhao;  Yang Cao;  Yu Kang;  Zhen-Yi Xu
Adobe PDF(1649Kb)  |  收藏  |  浏览/下载：127/43  |  提交时间：2021/04/22
Vehicle emission prediction  spatiotemporal gragh convolution  GPS trajectories  motor vehicle emission simulator (MOVES) model  feature sharing  
Investigating the dynamic memory effect of human drivers via ON-LSTM 期刊论文
SCIENCE CHINA-INFORMATION SCIENCES, 2020, 卷号: 63, 期号: 9, 页码: 11
作者:  Dai, Shengzhe;  Li, Zhiheng;  Li, Li;  Cao, Dongpu;  Dai, Xingyuan;  Lin, Yilun
Adobe PDF(325Kb)  |  收藏  |  浏览/下载：255/45  |  提交时间：2020/12/04
driving behavior  memory effect  trajectory prediction  historical information  ON-LSTM  
Pedestrian Choice Modeling and Simulation of Staged Evacuation Strategies in Daya Bay Nuclear Power Plant 期刊论文
EEE Transactions on Computational Social Systems, 2020, 卷号: 7, 期号: 3, 页码: 686-695
作者:  Yang, Linyao;  Wang, Xiao;  Zhang, Jun Jason;  Zhou, Min;  Wang, Fei-Yue
Adobe PDF(2409Kb)  |  收藏  |  浏览/下载：138/48  |  提交时间：2022/06/15
Agent-based modeling  exit choice  pedestrian crowd evacuation  random forest (RF)  staged evacuation  
Face Detection With Different Scales Based on Faster R-CNN 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2019, 卷号: 49, 期号: 11, 页码: 4017-4028
作者:  Wu, Wenqi;  Yin, Yingjie;  Wang, Xingang;  Xu, De
浏览  |  Adobe PDF(2762Kb)  |  收藏  |  浏览/下载：462/144  |  提交时间：2018/10/02
Deep convolutional neural network (DCNN)  deep learning  face detection  Faster R-CNN  
A Radiomics Nomogram for Preoperative Prediction of Microvascular Invasion in Hepatocellular Carcinoma 期刊论文
LIVER CANCER, 2019, 卷号: 8, 期号: 5, 页码: 373-386
作者:  Yang, Li;  Gu, Dongsheng;  Wei, Jingwei;  Yang, Chun;  Rao, Shengxiang;  Wang, Wentao;  Chen, Caizhong;  Ding, Ying;  Tian, Jie;  Zeng, Mengsu
Adobe PDF(1052Kb)  |  收藏  |  浏览/下载：332/55  |  提交时间：2019/12/16
Microvascular invasion  Hepatocellular carcinoma  Gadoxetic acid  Radiomics  Nomogram  
Capturing Car-Following Behaviors by Deep Learning 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2018, 卷号: 19, 期号: 3, 页码: 910-920
作者:  Wang, Xiao;  Jiang, Rui;  Li, Li;  Lin, Yilun;  Zheng, Xinhu;  Wang, Fei-Yue
浏览  |  Adobe PDF(3543Kb)  |  收藏  |  浏览/下载：429/167  |  提交时间：2018/10/10
Microscopic Car-following Model  Deep Learning  Recurrent Neural Network (Rnn)  Gated Recurrent Unit (Gru) Neural Networks