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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：202/48  |  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：245/55  |  提交时间：2021/11/26
Disguised voice recognition  deep belief network  feature extraction  Gammatone frequency cepstrum coefficients (GFCC)  dropout  
Fault Information Recognition for On-board Equipment of High-speed Railway Based on Multi-neural Network Collaboration 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 6, 页码: 935-946
作者:  Lu-Jie Zhou;  Jian-Wu Dang;  Zhen-Hai Zhang
Adobe PDF(1263Kb)  |  收藏  |  浏览/下载：257/58  |  提交时间：2021/11/26
Train control system  Chinese named entity recognition (NER)  character feature  gating mechanism  bidirectional long short-term memory (BiLSTM)  
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：254/53  |  提交时间：2021/11/26
Abdominal organ, supervised segmentation  semi-supervised segmentation  evaluation metrics  image segmentation  machine learning  
STRNet: Triple-stream Spatiotemporal Relation Network for Action Recognition 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 5, 页码: 718-730
作者:  Zhi-Wei Xu;  Xiao-Jun Wu;  Josef Kittler
Adobe PDF(1129Kb)  |  收藏  |  浏览/下载：213/55  |  提交时间：2021/09/13
Action recognition  spatiotemporal relation  multi-branch fusion  long-term representation  video classification  
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：205/50  |  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：209/53  |  提交时间：2021/07/20
Self-supervised learning  contrastive learning  synthetic image  convolutional neural network  representation learning  
EDT Method for Multiple Labelled Objects Subject to Tied Distances 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 3, 页码: 468-479
作者:  Andre Marasca;  Andre Backes;  Fabio Favarim;  Marcelo Teixeira;  Dalcimar Casanova
Adobe PDF(2313Kb)  |  收藏  |  浏览/下载：283/62  |  提交时间：2021/05/24
Euclidean distance transform (EDT)  multiple-labelled objects  tied distances  fractal analysis  texture analysis  
Prediction of Spatiotemporal Evolution of Urban Traffic Emissions Based on Taxi Trajectories 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 2, 页码: 219-232
作者:  Zhen-Yi Zhao;  Yang Cao;  Yu Kang;  Zhen-Yi Xu
Adobe PDF(1649Kb)  |  收藏  |  浏览/下载：163/61  |  提交时间：2021/04/22
Vehicle emission prediction  spatiotemporal gragh convolution  GPS trajectories  motor vehicle emission simulator (MOVES) model  feature sharing  
A Brain-inspired SLAM System Based on ORB Features 期刊论文
International Journal of Automation and Computing, 2017, 卷号: 14, 期号: 5, 页码: 564-575
作者:  Sun-Chun Zhou;  Rui Yan;  Jia-Xin Li;  Ying-Ke Chen;  Huajin Tang
Adobe PDF(2451Kb)  |  收藏  |  浏览/下载：217/54  |  提交时间：2021/02/23
Simultaneous localization and mapping (SLAM)  RatSLAM  mobile robot  oriented features from accelerated segment test and rotated binary robust independent elementary (ORB) features of RGB (red, green, blue)  cognitive map.