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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：240/64  |  提交时间：2021/02/23
Computational intelligence  evolutionary computation  neural network  deep learning  remote sensing image registration  
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：277/42  |  提交时间：2021/05/24
Performance evaluation  neural architecture search  biometrics  palmprint  palm vein  deep learning  
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  
fMRI-based Decoding of Visual Information from Human Brain Activity: A Brief Review 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 2, 页码: 170-184
作者:  Shuo Huang;  Wei Shao;  Mei-Ling Wang;  Dao-Qiang Zhang
Adobe PDF(4328Kb)  |  收藏  |  浏览/下载：149/37  |  提交时间：2021/04/22
Functional magnetic resonance imaging (fMRI)  functional alignment  brain activity, brain decoding  visual stimuli reconstruction  
Robust Object Tracking via Information Theoretic Measures 期刊论文
International Journal of Automation and Computing, 2020, 期号: 17, 页码: 1
作者:  Wang, Weining;  Li, Qi;  Wang, Liang
浏览  |  Adobe PDF(9045Kb)  |  收藏  |  浏览/下载：178/51  |  提交时间：2020/09/03
Object tracking, information theoretic measures, correntropy, template update, robust to complex noises  
A Fast Compression Framework Based on 3D Point Cloud Data for Telepresence 期刊论文
International Journal of Automation and Computing, 2020, 卷号: 17, 期号: 6, 页码: 855-866
作者:  Zun-Ran Wang;  Chen-Guang Yang;  Shi-Lu Dai
浏览  |  Adobe PDF(1401Kb)  |  收藏  |  浏览/下载：188/63  |  提交时间：2021/02/22
3D point cloud compression  motion estimation  signatures of histograms orientation  3D point cloud matching  predicted frame and intra frame.  
Robust Object Tracking via Information Theoretic Measures 期刊论文
International Journal of Automation and Computing, 2020, 卷号: 17, 期号: 5, 页码: 652-666
作者:  Wei-Ning Wang;  Qi Li;  Liang Wang
Adobe PDF(1855Kb)  |  收藏  |  浏览/下载：146/15  |  提交时间：2021/02/22
Object tracking  information theoretic measures  correntropy  template update  robust to complex noises.  
Electronic Nose and Its Applications: A Survey 期刊论文
International Journal of Automation and Computing, 2020, 卷号: 17, 期号: 2, 页码: 179-209
作者:  Diclehan Karakaya;  Oguzhan Ulucan;  Mehmet Turkan
浏览  |  Adobe PDF(1365Kb)  |  收藏  |  浏览/下载：167/32  |  提交时间：2021/02/22
Artificial intelligence  machine learning  pattern recognition  electronic nose (EN)  sensors technology.  
Image Encryption Algorithm Based on Compressive Sensing and Fractional DCT via Polynomial Interpolation 期刊论文
International Journal of Automation and Computing, 2020, 卷号: 17, 期号: 2, 页码: 292-304
作者:  Ya-Ru Liang;  Zhi-Yong Xiao
浏览  |  Adobe PDF(1665Kb)  |  收藏  |  浏览/下载：137/54  |  提交时间：2021/02/22
Compressive sensing  fractional discrete cosine transform (DCT) via polynomial interpolation  image encryption  three-dimensional piecewise and nonlinear chaotic maps  real-valued output.  
Deep Learning Based Single Image Super-resolution: A Survey 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 4, 页码: 413-426
作者:  Viet Khanh Ha;  Jin-Chang Ren;  Xin-Ying Xu;  Sophia Zhao;  Gang Xie;  Valentin Masero;  Amir Hussain
浏览  |  Adobe PDF(1389Kb)  |  收藏  |  浏览/下载：114/30  |  提交时间：2021/02/22
Image super-resolution  convolutional neural network  high-resolution image  low-resolution image  deep learning.