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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：251/64  |  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：285/42  |  提交时间：2021/05/24
Performance evaluation  neural architecture search  biometrics  palmprint  palm vein  deep learning  
Deep Audio-Visual Learning: A Survey 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 3, 页码: 351-376
作者:  Hao Zhu;  Man-Di Luo;  Rui Wang;  Ai-Hua Zheng;  Ran He
Adobe PDF(1864Kb)  |  收藏  |  浏览/下载：194/38  |  提交时间：2021/05/24
Deep audio-visual learning  audio-visual separation and localization  correspondence learning  generative models  representation learning  
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：260/38  |  提交时间：2021/05/24
Deep learning  visual tracking  data-invariant  data-adaptive  general components  
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：213/48  |  提交时间：2021/11/26
Abdominal organ, supervised segmentation  semi-supervised segmentation  evaluation metrics  image segmentation  machine learning  
DLA+: A Light Aggregation Network for Object Classification and Detection 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 6, 页码: 963-972
作者:  Fu-Tian Wang;  Li Yang;  Jin Tang;  Si-Bao Chen;  Xin Wang
Adobe PDF(1212Kb)  |  收藏  |  浏览/下载：174/28  |  提交时间：2021/11/26
Light weight  image classification  channel attention  efficient convolution  object detection  
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：170/41  |  提交时间：2021/09/13
Action recognition  spatiotemporal relation  multi-branch fusion  long-term representation  video classification  
Spectral-spatial Classification of Hyperspectral Images Using Signal Subspace Identification and Edge-preserving Filter 期刊论文
International Journal of Automation and Computing, 2020, 卷号: 17, 期号: 2, 页码: 222-232
作者:  Negin Alborzi;  Fereshteh Poorahangaryan;  Homayoun Beheshti
浏览  |  Adobe PDF(1128Kb)  |  收藏  |  浏览/下载：150/47  |  提交时间：2021/02/22
Hyperspectral image  remote sensing  the hyperspectral signal subspace identification (HYSIME)  edge-preserving filter  classification  support vector machine.  
Skeleton Marching-based Parallel Vascular Geometry Reconstruction Using Implicit Functions 期刊论文
International Journal of Automation and Computing, 2020, 卷号: 17, 期号: 1, 页码: 30-43
作者:  Quan Qi;  Qing-De Li;  Yongqiang Cheng;  Qing-Qi Hong
浏览  |  Adobe PDF(2182Kb)  |  收藏  |  浏览/下载：106/38  |  提交时间：2021/02/22
Vascular geometric reconstruction  implicit modelling  parallel computing  high-performance  high-accuracy.  
Adversarial Attacks and Defenses in Images, Graphs and Text: A Review 期刊论文
International Journal of Automation and Computing, 2020, 卷号: 17, 期号: 2, 页码: 151-178
作者:  Han Xu;  Yao Ma;  Hao-Chen Liu;  Debayan Deb;  Hui Liu;  Ji-Liang Tang;  Anil K. Jain
浏览  |  Adobe PDF(2155Kb)  |  收藏  |  浏览/下载：202/57  |  提交时间：2021/02/22
Adversarial example  model safety  robustness  defenses  deep learning.