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CASIA OpenIR
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Hierarchical Fused Model With Deep Learning and Type-2 Fuzzy Learning for Breast Cancer Diagnosis 期刊论文
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2020, 卷号: 28, 期号: 12, 页码: 3204-3218
作者:  Shen, Tianyu;  Wang, Jiangong;  Gou, Chao;  Wang, Fei-Yue
Adobe PDF(3530Kb)  |  收藏  |  浏览/下载：343/76  |  提交时间：2021/03/02
Image segmentation  Biomedical imaging  Fuzzy sets  Breast cancer  Breast cancer  deep learning (DL)  fuzzy classifier (FC)  interval type-2 possibilistic fuzzy c-means (IT2PFCM)  
Accelerating Minibatch Stochastic Gradient Descent Using Typicality Sampling 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 卷号: 31, 期号: 11, 页码: 4649-4659
作者:  Peng, Xinyu;  Li, Li;  Wang, Fei-Yue
收藏  |  浏览/下载：260/0  |  提交时间：2021/01/06
Training  Convergence  Approximation algorithms  Stochastic processes  Estimation  Optimization  Acceleration  Batch selection  machine learning  minibatch stochastic gradient descent (SGD)  speed of convergence  
Parallel Control for Optimal Tracking via Adaptive Dynamic Programming 期刊论文
IEEE-CAA JOURNAL OF AUTOMATICA SINICA, 2020, 卷号: 7, 期号: 6, 页码: 1662-1674
作者:  Lu, Jingwei;  Wei, Qinglai;  Wang, Fei-Yue
浏览  |  Adobe PDF(7214Kb)  |  收藏  |  浏览/下载：363/66  |  提交时间：2021/01/06
Adaptive dynamic programming (ADP)  nonlinear optimal control  parallel controller  parallel control theory  parallel system  tracking control  neural network (NN)  
Acting As A Decision Maker: Traffic-Condition-Aware Ensemble Learning for Traffic Flow Prediction 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2020, 期号: Accepted, 页码: Accepted
作者:  Yuanyuan Chen;  Hongyu Chen;  Peijun Ye;  Yisheng Lv;  Fei-Yue Wang
浏览  |  Adobe PDF(2382Kb)  |  收藏  |  浏览/下载：303/63  |  提交时间：2020/10/16
Traffic Flow Prediction  Ensemble Learning  Deep Learning  
Parallel Transportation Systems: Toward IoT-Enabled Smart Urban Traffic Control and Management 期刊论文
IEEE Transactions on Intelligent Transportation Systems, 2020, 卷号: 21, 期号: 10, 页码: 4063 - 4071
作者:  Fenghua Zhu;  Yisheng Lv;  Yuanyuan Chen;  Xiao Wang;  Gang Xiong;  Fei-Yue Wang
浏览  |  Adobe PDF(2879Kb)  |  收藏  |  浏览/下载：484/236  |  提交时间：2020/10/15
Intelligent transportation systems  
Decision-Making in Driver-Automation Shared Control: A Review and Perspectives 期刊论文
IEEE-CAA JOURNAL OF AUTOMATICA SINICA, 2020, 卷号: 7, 期号: 5, 页码: 1289-1307
作者:  Wang, Wenshuo;  Na, Xiaoxiang;  Cao, Dongpu;  Gong, Jianwei;  Xi, Junqiang;  Xing, Yang;  Wang, Fei-Yue
浏览  |  Adobe PDF(14998Kb)  |  收藏  |  浏览/下载：262/31  |  提交时间：2020/09/07
Automated vehicle  decision-making  human driver  human-vehicle interaction  shared control  
Parallel control for continuous-time linear systems: A case study 期刊论文
IEEE-CAA JOURNAL OF AUTOMATICA SINICA, 2020, 卷号: 7, 期号: 4, 页码: 919-928
作者:  Wei, Qinglai;  Li, Hongyang;  Wang, Fei-Yue
Adobe PDF(4146Kb)  |  收藏  |  浏览/下载：290/38  |  提交时间：2020/08/03
Continuous-time linear systems  digital twin  parallel controller  parallel intelligence  parallel systems  
A parallel vision approach to scene-specific pedestrian detection 期刊论文
NEUROCOMPUTING, 2020, 卷号: 394, 页码: 114-126
作者:  Zhang, Wenwen;  Wang, Kunfeng;  Liu, Yating;  Lu, Yue;  Wang, Fei-Yue
Adobe PDF(4090Kb)  |  收藏  |  浏览/下载：377/55  |  提交时间：2020/06/22
Pedestrian detection  Specific scene  Synthetic data  Video surveillance  Parallel vision  
A Recurrent Attention and Interaction Model for Pedestrian Trajectory Prediction 期刊论文
Journal of Automatica Sinica, 2020, 期号: *, 页码: *
作者:  Li Xuesong;  Liu Yating;  Wang Kunfeng;  Wang Fei-Yue
浏览  |  Adobe PDF(5533Kb)  |  收藏  |  浏览/下载：177/52  |  提交时间：2020/06/08
Trajectory prediction  recurrent attention and interaction model  Long Short-Term Memory  deep learning  
Parallel reinforcement learning-based energy efficiency improvement for a cyber-physical system 期刊论文
IEEE-CAA JOURNAL OF AUTOMATICA SINICA, 2020, 卷号: 7, 期号: 2, 页码: 617-626
作者:  Liu, Teng;  Tian, Bin;  Ai, Yunfeng;  Wang, Fei-Yue
Adobe PDF(5784Kb)  |  收藏  |  浏览/下载：261/6  |  提交时间：2020/06/02
Bidirectional long short-term memory (LSTM) network  cyber-physical system (CPS)  energy management  parallel system  reinforcement learning (RL)