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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：175/41  |  提交时间：2021/07/20
Self-supervised learning  contrastive learning  synthetic image  convolutional neural network  representation 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：210/76  |  提交时间：2021/02/23
Performance evaluation  convolutional neural network (CNN)  biometrics  palmprint  palm vein  deep learning  
Hidden Markov Model Approach for Software Reliability Estimation with Logic Error 期刊论文
International Journal of Automation and Computing, 2020, 卷号: 17, 期号: 2, 页码: 305-320
作者:  R. Bharathi;  R. Selvarani
浏览  |  Adobe PDF(1248Kb)  |  收藏  |  浏览/下载：179/66  |  提交时间：2021/02/22
Hidden Markov model (HMM)  reliability  logic error  safety critical  software failure.  
Output Feedback Stabilization for MIMO Semi-linear Stochastic Systems with Transient Optimisation 期刊论文
International Journal of Automation and Computing, 2020, 卷号: 17, 期号: 1, 页码: 83-95
作者:  Qi-Chun Zhang;  Liang Hu;  John Gow
浏览  |  Adobe PDF(1322Kb)  |  收藏  |  浏览/下载：106/37  |  提交时间：2021/02/22
Multi-input-multi-output (MIMO) stochastic systems  output feedback stabilisation  block backstepping  randomness attenuation  probabilistic decoupling  mutual information.  
Performance Evaluation and Improvement of Chipset Assembly & Test Production Line Based on Variability 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 2, 页码: 186-198
作者:  Chang-Jun Li;  Zong-Shi Xie;  Xin-Ran Peng;  Bo Li
浏览  |  Adobe PDF(1239Kb)  |  收藏  |  浏览/下载：116/38  |  提交时间：2021/02/22
Performance evaluation and improvement  chipset assembly & test production line (CATPL)  parameters  Little′s law  variability.