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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：267/59  |  提交时间：2020/06/20
Speech emotion recognition  the ladder network  semi-supervised learning  autoencoder  regularization  
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
Adobe PDF(1389Kb)  |  收藏  |  浏览/下载：119/31  |  提交时间：2021/02/22
Image super-resolution  convolutional neural network  high-resolution image  low-resolution image  deep learning.  
Fuzzy Behavior-based Control of Three Wheeled Omnidirectional Mobile Robot 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 2, 页码: 163-185
作者:  Nacer Hacene;  Boubekeur Mendil
Adobe PDF(3450Kb)  |  收藏  |  浏览/下载：118/45  |  提交时间：2021/02/22
Three wheeled omnidirectional mobile robot (TWOMR)  autonomous navigation  obstacle avoidance  fuzzy behavior-based control  dynamic target  dynamic environment.  
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：109/39  |  提交时间：2021/02/22
Human computation  speech analysis  crowdsourcing  gamified data collection  survey.  
Transfer Hierarchical Attention Network for Generative Dialog System 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 6, 页码: 720-736
作者:  Xiang Zhang;  Qiang Yang
浏览  |  Adobe PDF(1145Kb)  |  收藏  |  浏览/下载：84/28  |  提交时间：2021/02/22
Dialog system  transfer learning  deep learning  natural language processing (NLP)  artificial intelligence.  
Development of STEP AP224 Extractor for Interfacing Feature Based CAPP to STEP-NC (AP238) 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 5, 页码: 655-670
作者:  Deepanshu Srivastava;  Venkateswara Rao Komma
浏览  |  Adobe PDF(3913Kb)  |  收藏  |  浏览/下载：109/38  |  提交时间：2021/02/22
Reduced-order observer  discrete-time systems  Lipschitz systems  H∞  ARDUINO MEGA 2560 device.  
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：174/53  |  提交时间：2021/02/22
Feature engineering  sensor data analysis  Internet of things (IoT) analytics  interpretable learning  automation.  
An Advanced Analysis System for Identifying Alcoholic Brain State Through EEG Signals 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 6, 页码: 737-747
作者:  Siuly Siuly;  Varun Bajaj;  Abdulkadir Sengur;  Yanchun Zhang
浏览  |  Adobe PDF(4171Kb)  |  收藏  |  浏览/下载：143/48  |  提交时间：2021/02/22
Electroencephalogram (EEG)  alcoholism  optimum allocation technique  feature extraction  decision table.  
Synthesizing Robot Programs with Interactive Tutor Mode 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 4, 页码: 462-474
作者:  Hao Li;  Yu-Ping Wang;  Tai-Jiang Mu
浏览  |  Adobe PDF(1023Kb)  |  收藏  |  浏览/下载：118/47  |  提交时间：2021/02/22
Human-robot interaction  semantic parsing  program synthesis  intelligent robotic systems  natural language understanding.  
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：123/40  |  提交时间：2021/02/22
Performance evaluation and improvement  chipset assembly & test production line (CATPL)  parameters  Little′s law  variability.