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Data Augmentation and Deep Neuro-fuzzy Network for Student Performance Prediction with MapReduce Framework 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 6, 页码: 981-992
作者:  Amlan Jyoti Baruah;  Siddhartha Baruah
Adobe PDF(1583Kb)  |  收藏  |  浏览/下载：198/50  |  提交时间：2021/11/26
Educational data mining (EDA)  MapReduce framework  deep neuro-fuzzy network  student performance  data augmentation  
A Signal Based “W” Structural Elements for Multi-scale Mathematical Morphology Analysis and Application to Fault Diagnosis of Rolling Bearings of Wind Turbines 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 6, 页码: 993-1006
作者:  Qiang Li;  Yong-Sheng Qi;  Xue-Jin Gao;  Yong-Ting Li;  Li-Qiang Liu
Adobe PDF(1828Kb)  |  收藏  |  浏览/下载：183/49  |  提交时间：2021/11/26
Fault diagnosis  structural element  multi-scale mathematical morphology  rolling bearing  correlation analysis  
Encoding-decoding Network With Pyramid Self-attention Module for Retinal Vessel Segmentation 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 6, 页码: 973-980
作者:  Cong-Zhong Wu;  Jun Sun;  Jing Wang;  Liang-Feng Xu;  Shu Zhan
Adobe PDF(1416Kb)  |  收藏  |  浏览/下载：166/38  |  提交时间：2021/11/26
Retina vessel segmentation  deep learning  U-Net  attention mechanism  medical image  
Research on Voiceprint Recognition of Camouflage Voice Based on Deep Belief Network 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 6, 页码: 947-962
作者:  Nan Jiang;  Ting Liu
Adobe PDF(1905Kb)  |  收藏  |  浏览/下载：206/46  |  提交时间：2021/11/26
Disguised voice recognition  deep belief network  feature extraction  Gammatone frequency cepstrum coefficients (GFCC)  dropout  
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：219/48  |  提交时间：2021/11/26
Abdominal organ, supervised segmentation  semi-supervised segmentation  evaluation metrics  image segmentation  machine learning  
Dynamic Event-triggered Control and Estimation: A Survey 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 6, 页码: 857-886
作者:  Xiaohua Ge;  Qing-Long Han;  Xian-Ming Zhang;  Derui Ding
Adobe PDF(3887Kb)  |  收藏  |  浏览/下载：203/39  |  提交时间：2021/11/26
Networked systems  dynamic event-triggered control  dynamic event-triggered estimation  dynamic event-triggered mechanisms  vehicle active suspension system  water distribution and supply system  
Fault Classification for On-board Equipment of High-speed Railway Based on Attention Capsule Network 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 5, 页码: 814-825
作者:  Lu-Jie Zhou;  Jian-Wu Dang;  Zhen-Hai Zhan
Adobe PDF(1208Kb)  |  收藏  |  浏览/下载：224/52  |  提交时间：2021/09/13
On-board equipment  fault classification  capsule network  attention mechanism  focal loss  
A Fast Vision-inertial Odometer Based on Line Midpoint Descriptor 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 4, 页码: 667-669
作者:  Wen-Kuan Li;  Hao-Yuan Cai;  Sheng-Lin Zhao;  Ya-Qian Liu;  Chun-Xiu Liu
Adobe PDF(10350Kb)  |  收藏  |  浏览/下载：179/40  |  提交时间：2021/07/20
High efficiency  visual-inertial odometry (VIO)  non-linear optimization  points and lines  sliding window  
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：183/41  |  提交时间：2021/07/20
Self-supervised learning  contrastive learning  synthetic image  convolutional neural network  representation learning  
A Review on Cooperative Robotic Arms with Mobile or Drones Bases 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 4, 页码: 536-555
作者:  Larona Pitso Ramalepa;  Rodrigo S. Jamisola Jr.
Adobe PDF(1192Kb)  |  收藏  |  浏览/下载：491/341  |  提交时间：2021/07/20
Cooperative arms  mobile manipulator  aerial manipulator  mobile base  drone base  cooperative tasks