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Fault Classification for On-board Equipment of High-speed Railway Based on Attention Capsule Network 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 5, 页码: 814-825
作者:  Lu-Jie Zhou;  Jian-Wu Dang;  Zhen-Hai Zhan
Adobe PDF(1208Kb)  |  收藏  |  浏览/下载：217/51  |  提交时间：2021/09/13
On-board equipment  fault classification  capsule network  attention mechanism  focal loss  
A Spatial Cognitive Model that Integrates the Effects of Endogenous and Exogenous Information on the Hippocampus and Striatum 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 4, 页码: 632-644
作者:  Jing Huang;  He-Yuan Yang;  Xiao-Gang Ruan;  Nai-Gong Yu;  Guo-Yu Zuo;  Hao-Meng Liu
Adobe PDF(1915Kb)  |  收藏  |  浏览/下载：187/54  |  提交时间：2021/07/20
Exogenous and endogenous information  hippocampus, striatum  spatial cognition  brain-inspired computation  
A Novel Heterogeneous Actor-critic Algorithm with Recent Emphasizing Replay Memory 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 4, 页码: 619-631
作者:  Bao Xi;  Rui Wang;  Ying-Hao Cai;  TaoLu;  Shuo Wang
Adobe PDF(2505Kb)  |  收藏  |  浏览/下载：164/50  |  提交时间：2021/07/20
Reinforcement learning (RL)  actor-critic  experience replay  training efficiency  manipulation skill learning  
A Review on Cooperative Robotic Arms with Mobile or Drones Bases 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 4, 页码: 536-555
作者:  Larona Pitso Ramalepa;  Rodrigo S. Jamisola Jr.
Adobe PDF(1192Kb)  |  收藏  |  浏览/下载：487/340  |  提交时间：2021/07/20
Cooperative arms  mobile manipulator  aerial manipulator  mobile base  drone base  cooperative tasks  
Ensuring the Correctness of Regular Expressions: A Review 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 4, 页码: 521-535
作者:  Li-Xiao Zheng;  Shuai Ma;  Zu-Xi Chen;  Xiang-Yu Luo
Adobe PDF(1076Kb)  |  收藏  |  浏览/下载：114/31  |  提交时间：2021/07/20
Regular expressions  correctness  string generation  learning  static checking  verification  visualization, repairing  
Fire Detection Method Based on Depthwise Separable Convolution and YOLOv3 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 2, 页码: 300-310
作者:  Yue-Yan Qin;  Jiang-Tao Cao;  Xiao-Fei Ji
Adobe PDF(2289Kb)  |  收藏  |  浏览/下载：181/54  |  提交时间：2021/04/22
Fire detection  depthwise separable convolution  fire classification  You Only Look Once version 3 (YOLOv3)  target regression  
Suction-based Grasp Point Estimation in Cluttered Environment for Robotic Manipulator Using Deep Learning-based Affordance Map 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 2, 页码: 277-287
作者:  Tri Wahyu Utomo, Adha Imam Cahyadi, Igi Ardiyanto
Adobe PDF(913Kb)  |  收藏  |  浏览/下载：150/54  |  提交时间：2021/04/22
Grasping point estimation  household objects  red, green, blue and depth (RGBD) channel image  semantic segmentation  cluttered environment  
Humans and Robots: A Mutually Inclusive Relationship in a Contagious World 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 2, 页码: 185-203
作者:  Akash Gupta;  Anshuman Singh;  Deepak Bharadwaj;  Amit Kumar Mondal
Adobe PDF(1295Kb)  |  收藏  |  浏览/下载：205/54  |  提交时间：2021/04/22
COVID-19  coronavirus  telepresence  delivery robots  medical robots  
Event-based Control and Filtering of Networked Systems: A Survey 期刊论文
International Journal of Automation and Computing, 2017, 卷号: 14, 期号: 3, 页码: 239-253
作者:  Lei Zou;  Zi-Dong Wang;  Dong-Hua Zhou
浏览  |  Adobe PDF(3631Kb)  |  收藏  |  浏览/下载：166/36  |  提交时间：2021/02/23
Event-triggered transmission  networked systems  event-based control  event-based filtering  event-triggered distributed state estimation  distributed control with event-based protocol.  
Learning to Transform Service Instructions into Actions with Reinforcement Learning and Knowledge Base 期刊论文
International Journal of Automation and Computing, 2018, 卷号: 15, 期号: 5, 页码: 582-592
作者:  Meng-Yang Zhang;  Guo-Hui Tian;  Ci-Ci Li;  Jing Gong
浏览  |  Adobe PDF(975Kb)  |  收藏  |  浏览/下载：97/41  |  提交时间：2021/02/23
Natural language  robot  knowledge base  reinforcement learning  object state.