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Computational Intelligence in Remote Sensing Image Registration: A survey 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 1, 页码: 1-17
作者:  Yue Wu;  Jun-Wei Liu;  Chen-Zhuo Zhu;  Zhuang-Fei Bai;  Qi-Guang Miao;  Wen-Ping Ma;  Mao-Guo Gong
浏览  |  Adobe PDF(995Kb)  |  收藏  |  浏览/下载:238/63  |  提交时间:2021/02/23
Computational intelligence  evolutionary computation  neural network  deep learning  remote sensing image registration  
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:478/338  |  提交时间:2021/07/20
Cooperative arms  mobile manipulator  aerial manipulator  mobile base  drone base  cooperative tasks  
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:520/310  |  提交时间:2021/05/24
Signalized intersection  driving behaviour  machine learning  support vector machine (SVM)  road accidents  
Advances in Deep Learning Methods for Visual Tracking: Literature Review and Fundamentals 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 3, 页码: 311-333
作者:  Xiao-Qin Zhang;  Run-Hua Jiang;  Chen-Xiang Fan;  Tian-Yu Tong;  Tao Wang Peng-Cheng Huang
Adobe PDF(1787Kb)  |  收藏  |  浏览/下载:256/37  |  提交时间:2021/05/24
Deep learning  visual tracking  data-invariant  data-adaptive  general components  
Contrastive Self-supervised Representation Learning Using Synthetic Data 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 4, 页码: 556-567
作者:  Dong-Yu She;  Kun Xu
Adobe PDF(993Kb)  |  收藏  |  浏览/下载:176/41  |  提交时间:2021/07/20
Self-supervised learning  contrastive learning  synthetic image  convolutional neural network  representation learning  
Hybrid Approach to Document Anomaly Detection: An Application to Facilitate RPA in Title Insurance 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 1, 页码: 55-72
作者:  Abhijit Guha;  Debabrata Samanta
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Anomaly detection  title insurance  autoencoder  one-class support vector machine (OSVM)  term frequency – inverse document frequency (TF-IDF)  robotic process automation  dimensionality reduction  
A Performance Evaluation of Classic Convolutional Neural Networks for 2D and 3D Palmprint and Palm Vein Recognition 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 1, 页码: 18-44
作者:  Wei Jia;  Jian Gao;  Wei Xia;  Yang Zhao;  Hai Min;  Jing-Ting Lu
浏览  |  Adobe PDF(2680Kb)  |  收藏  |  浏览/下载:212/76  |  提交时间:2021/02/23
Performance evaluation  convolutional neural network (CNN)  biometrics  palmprint  palm vein  deep learning  
Research on Voiceprint Recognition of Camouflage Voice Based on Deep Belief Network 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 6, 页码: 947-962
作者:  Nan Jiang;  Ting Liu
Adobe PDF(1905Kb)  |  收藏  |  浏览/下载:189/41  |  提交时间:2021/11/26
Disguised voice recognition  deep belief network  feature extraction  Gammatone frequency cepstrum coefficients (GFCC)  dropout  
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:167/39  |  提交时间:2021/09/13
Action recognition  spatiotemporal relation  multi-branch fusion  long-term representation  video classification  
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:209/49  |  提交时间:2021/09/13
On-board equipment  fault classification  capsule network  attention mechanism  focal loss