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EDT Method for Multiple Labelled Objects Subject to Tied Distances 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 3, 页码: 468-479
作者:  Andre Marasca;  Andre Backes;  Fabio Favarim;  Marcelo Teixeira;  Dalcimar Casanova
Adobe PDF(2313Kb)  |  收藏  |  浏览/下载:247/50  |  提交时间:2021/05/24
Euclidean distance transform (EDT)  multiple-labelled objects  tied distances  fractal analysis  texture analysis  
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
Adobe PDF(995Kb)  |  收藏  |  浏览/下载:235/63  |  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  
2D and 3D Palmprint and Palm Vein Recognition Based on Neural Architecture Search 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 3, 页码: 377-409
作者:  Wei Jia;  Wei Xia;  Yang Zhao;  Hai Min;  Yan-Xiang Chen
Adobe PDF(15758Kb)  |  收藏  |  浏览/下载:273/41  |  提交时间:2021/05/24
Performance evaluation  neural architecture search  biometrics  palmprint  palm vein  deep learning  
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:250/49  |  提交时间:2021/05/24
Person re-identification (Re-ID)  thermal infrared  generative networks  attention  deep 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  
Event-triggered Control of Positive Switched Systems with Actuator Saturation and Time-delay 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 1, 页码: 141-154
作者:  Jun-Feng Zhang;  Lai-You Liu;  Shi-Zhou Fu;  Shuo Li
Adobe PDF(1357Kb)  |  收藏  |  浏览/下载:302/159  |  提交时间:2021/02/23
Positive switched systems  event-triggered control  randomly occurring actuator saturation  linear programming  time-delay  
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
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Performance evaluation  convolutional neural network (CNN)  biometrics  palmprint  palm vein  deep learning  
A Position Synchronization Controller for Co-ordinated Links (COOL) Dual Robot Arm Based on Integral Sliding Mode: Design and Experimental Validation 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 1, 页码: 110-123
作者:  Sumi Phukan;  Chitralekha Mahanta
浏览  |  Adobe PDF(7143Kb)  |  收藏  |  浏览/下载:147/27  |  提交时间:2021/02/23
Integral sliding mode control  position synchronization  dual-arm robotic manipulator  chattering  robust control  
Supervised and Semi-supervised Methods for Abdominalm Organ Segmentation: A Review 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 6, 页码: 887-914
作者:  Isaac Baffour Senkyire;  Zhe Liu
Adobe PDF(1308Kb)  |  收藏  |  浏览/下载:203/45  |  提交时间:2021/11/26
Abdominal organ, supervised segmentation  semi-supervised segmentation  evaluation metrics  image segmentation  machine learning