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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：190/57  |  提交时间：2021/02/22
Feature engineering  sensor data analysis  Internet of things (IoT) analytics  interpretable learning  automation.  
An Integrated MCI Detection Framework Based on Spectral-temporal Analysis 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 6, 页码: 786-799
作者:  Jiao Yin;  Jinli Cao;  Siuly Siuly;  Hua Wang
浏览  |  Adobe PDF(2203Kb)  |  收藏  |  浏览/下载：161/46  |  提交时间：2021/02/22
Electroencephalogram (EEG)  dementia early detection  mild cognitive impairment (MCI)  stationary wavelet transformation (SWT)  support vector machine (SVM).  
Large-scale Data Collection and Analysis via a Gamified Intelligent Crowdsourcing Platform 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 4, 页码: 427-436
作者:  Simone Hantke;  Tobias Olenyi;  Christoph Hausner;  Tobias Appel;  Björn Schuller
浏览  |  Adobe PDF(1345Kb)  |  收藏  |  浏览/下载：114/41  |  提交时间：2021/02/22
Human computation  speech analysis  crowdsourcing  gamified data collection  survey.  
Virtual Plate Based Controlling Strategy of Toy Play for Robot's Communication Development in JA Space 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 1, 页码: 93-101
作者:  Wei Wang;  Xiao-Dan Huang
浏览  |  Adobe PDF(2568Kb)  |  收藏  |  浏览/下载：109/46  |  提交时间：2021/02/22
Human robot cooperation  joint attention (JA) space  reachable space  toy play ability  a virtual plate.  
Semi-supervised Ladder Networks for Speech Emotion Recognition 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 4, 页码: 437-448
作者:  Tao, Jianhua;  Huang, Jian;  Li, Ya;  Lian, Zheng;  Niu, Mingyue
浏览  |  Adobe PDF(1025Kb)  |  收藏  |  浏览/下载：278/63  |  提交时间：2020/06/20
Speech emotion recognition  the ladder network  semi-supervised learning  autoencoder  regularization