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Fault Information Recognition for On-board Equipment of High-speed Railway Based on Multi-neural Network Collaboration 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 6, 页码: 935-946
作者:  Lu-Jie Zhou;  Jian-Wu Dang;  Zhen-Hai Zhang
Adobe PDF(1263Kb)  |  收藏  |  浏览/下载：213/46  |  提交时间：2021/11/26
Train control system  Chinese named entity recognition (NER)  character feature  gating mechanism  bidirectional long short-term memory (BiLSTM)  
STRNet: Triple-stream Spatiotemporal Relation Network for Action Recognition 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 5, 页码: 718-730
作者:  Zhi-Wei Xu;  Xiao-Jun Wu;  Josef Kittler
Adobe PDF(1129Kb)  |  收藏  |  浏览/下载：177/44  |  提交时间：2021/09/13
Action recognition  spatiotemporal relation  multi-branch fusion  long-term representation  video classification  
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：110/43  |  提交时间：2021/02/23
Natural language  robot  knowledge base  reinforcement learning  object state.  
A Novel Active Learning Method Using SVM for Text Classification 期刊论文
International Journal of Automation and Computing, 2018, 卷号: 15, 期号: 3, 页码: 290-298
作者:  Mohamed Goudjil;  Mouloud Koudil1 Mouldi Bedda;  Noureddine Ghoggali
浏览  |  Adobe PDF(720Kb)  |  收藏  |  浏览/下载：78/36  |  提交时间：2021/02/23
Text categorization  active learning  support vector machine (SVM)  pool-based active learning  pairwise coupling.  
A Wide Learning Approach for Interpretable Feature Recommendation for 1-D Sensor Data in IoT Analytics 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 6, 页码: 800-811
作者:  Snehasis Banerjee;  Tanushyam Chattopadhyay;  Utpal Garain
浏览  |  Adobe PDF(891Kb)  |  收藏  |  浏览/下载：186/56  |  提交时间：2021/02/22
Feature engineering  sensor data analysis  Internet of things (IoT) analytics  interpretable learning  automation.