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A Wide Learning Approach for Interpretable Feature Recommendation for 1-D Sensor Data in IoT Analytics 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 6, 页码: 800-811
作者:  Snehasis Banerjee;  Tanushyam Chattopadhyay;  Utpal Garain
浏览  |  Adobe PDF(891Kb)  |  收藏  |  浏览/下载：250/67  |  提交时间：2021/02/22
Feature engineering  sensor data analysis  Internet of things (IoT) analytics  interpretable learning  automation.  
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：159/42  |  提交时间：2021/02/22
Image super-resolution  convolutional neural network  high-resolution image  low-resolution image  deep learning.  
A Hybrid Time Frequency Response and Fuzzy Decision Tree for Non-stationary Signal Analysis and Pattern Recognition 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 3, 页码: 398-412
作者:  N. R. Nayak;  P. K. Dash;  R. Bisoi
浏览  |  Adobe PDF(1576Kb)  |  收藏  |  浏览/下载：164/54  |  提交时间：2021/02/22
Non-stationary signals  sparse S-transform (SST)  scaling method  fuzzy decision tree  pattern classification.  
An Approach to Reducing Input Parameter Volume for Fault Classifiers 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 2, 页码: 199-212
作者:  Ann Smith;  Fengshou Gu;  Andrew D. Ball
浏览  |  Adobe PDF(1085Kb)  |  收藏  |  浏览/下载：165/71  |  提交时间：2021/02/22
Fault diagnosis  classification  variable clustering  data compression  big data.