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Data Augmentation and Deep Neuro-fuzzy Network for Student Performance Prediction with MapReduce Framework 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 6, 页码: 981-992
作者:  Amlan Jyoti Baruah;  Siddhartha Baruah
Adobe PDF(1583Kb)  |  收藏  |  浏览/下载:229/53  |  提交时间:2021/11/26
Educational data mining (EDA)  MapReduce framework  deep neuro-fuzzy network  student performance  data augmentation  
Improved Network for Face Recognition Based on Feature Super Resolution Method 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 6, 页码: 915-925
作者:  Ling-Yi Xu;  Zoran Gajic
Adobe PDF(1989Kb)  |  收藏  |  浏览/下载:215/51  |  提交时间:2021/11/26
Face recognition  feature super resolution  multiple-branch network  deep learning  convolutional neural networks  
Dynamic Event-triggered Control and Estimation: A Survey 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 6, 页码: 857-886
作者:  Xiaohua Ge;  Qing-Long Han;  Xian-Ming Zhang;  Derui Ding
Adobe PDF(3887Kb)  |  收藏  |  浏览/下载:234/42  |  提交时间:2021/11/26
Networked systems  dynamic event-triggered control  dynamic event-triggered estimation  dynamic event-triggered mechanisms  vehicle active suspension system  water distribution and supply system  
Global FLS-based Consensus of Stochastic Uncertain Nonlinear Multi-agent Systems 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 5, 页码: 826-837
作者:  Jia-Xi Chen;  Jun-Min Li
Adobe PDF(2352Kb)  |  收藏  |  浏览/下载:244/57  |  提交时间:2021/09/13
Fuzzy logic systems  stochastic nonlinear  multi-agent systems (MAS)  consensus algorithm  adaptive control  
Dynamic System Identification of Underwater Vehicles Using Multi-output Gaussian Processes 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 5, 页码: 681-693
作者:  Wilmer Ariza Ramirez;  Juš Kocijan;  Zhi Quan Leong;  Hung Duc Nguyen;  Shantha Gamini Jayasinghe
Adobe PDF(3231Kb)  |  收藏  |  浏览/下载:249/56  |  提交时间:2021/09/13
Dependent Gaussian processes  dynamic system identification  multi-output Gaussian processes  non-parametric identification  autonomous underwater vehicle (AUV)  
Evolutionary Computation in Social Propagation over Complex Networks: A Survey 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 4, 页码: 503-520
作者:  Tian-Fang Zhao;  Wei-Neng Chen;  Xin-Xin Ma;  Xiao-Kun Wu
Adobe PDF(1283Kb)  |  收藏  |  浏览/下载:173/51  |  提交时间:2021/07/20
Evolutionary computation  complex network  propagation dynamics  social diffusion  evolution model  optimization algorithm  
Identification and classification of driving behaviour at a signalized intersection using support vector machine 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 3, 页码: 480-491
作者:  Soni Lanka Karri;  Liyanage Chandratilak De Silva;  Daphne Teck Ching Lai;  Shiaw Yin Yong
Adobe PDF(1497Kb)  |  收藏  |  浏览/下载:578/325  |  提交时间:2021/05/24
Signalized intersection  driving behaviour  machine learning  support vector machine (SVM)  road accidents  
Learning Deep RGBT Representations for Robust Person Re-identification 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 3, 页码: 443-456
作者:  Ai-Hua Zheng;  Zi-Han Chen;  Cheng-Long Li;  Jin Tang;  Bin Luo
Adobe PDF(1832Kb)  |  收藏  |  浏览/下载:298/68  |  提交时间:2021/05/24
Person re-identification (Re-ID)  thermal infrared  generative networks  attention  deep learning  
PokerNet: Expanding Features Cheaply via Depthwise Convolutions 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 3, 页码: 432-442
作者:  Wei Tang;  Yan Huang;  Liang Wang
Adobe PDF(1163Kb)  |  收藏  |  浏览/下载:247/41  |  提交时间:2021/05/24
Deep learning  depthwise convolution  lightweight deep model  model compression  model acceleration  
Optimal Policies for Quantum Markov Decision Processes 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 3, 页码: 410-421
作者:  Ming-Sheng Ying;  Yuan Feng;  Sheng-Gang Ying
Adobe PDF(1163Kb)  |  收藏  |  浏览/下载:270/58  |  提交时间:2021/05/24
Quantum Markov decision processes  quantum machine learning  reinforcement learning  dynamic programming  decision making