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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
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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.  
Inferring Functional Connectivity in fMRI Using Minimum Partial Correlation 期刊论文
International Journal of Automation and Computing, 2017, 卷号: 14, 期号: 4, 页码: 371-385
作者:  Lei Nie;  Xian Yang1 Pau(l);  M. Matthews;  Zhi-Wei Xu;  Yi-Ke Guo
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Functional connectivity  functional magnetic resonance imaging (fMRI)  network modelling  partial correlation  PCalgorithm  resting-state networks.  
PLS-CCA Heterogeneous Features Fusion-based Low-resolution Human Detection Method for Outdoor Video Surveillance 期刊论文
International Journal of Automation and Computing, 2017, 卷号: 14, 期号: 2, 页码: 136-146
作者:  Hong-Kai Chen;  Xiao-Guang Zhao;  Shi-Ying Sun;  Min Tan
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Low-resolution human detection  partial least squares  canonical correlation analysis  heterogeneous features  outdoor video surveillance.  
An Effective Density Based Approach to Detect Complex Data Clusters Using Notion of Neighborhood Difference 期刊论文
International Journal of Automation and Computing, 2017, 卷号: 14, 期号: 1, 页码: 57-67
作者:  S. Nagaraju;  Manish Kashyap;  Mahua Bhattachraya
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Density based clustering  neighborhood difference  density-based spatial clustering of applications with noise (DBSCAN)  space density indexing (SDI)  core object.  
An Advanced Prediction Mechanism to Analyse Pore Geometry Shapes and Identification of Blocking Effect in VRLA Battery System 期刊论文
International Journal of Automation and Computing, 2017, 卷号: 14, 期号: 1, 页码: 21-32
作者:  Alessandro Mariani;  Kary Thanapalan1 Peter Stevenson;  Jonathan Williams
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Positive active material  crystal structure  valve regulated lead acid (VRLA) batteries  modelling, estimation and recovery techniques.