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Covid-19 classification by FGCNet with deep feature fusion from graph convolutional network and convolutional neural network.

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第一作者： Shui-Hua,Wang

第一单位： Department of Cardiovascular Sciences, University of Leicester, LE1 7RH, UK.;Department of Information Systems, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia.;School of Architecture Building and Civil engineering, Loughborough University, Loughborough LE11 3TU, UK.

作者： Shui-Hua,Wang ^[1] ; Vishnu Varthanan,Govindaraj ^[2] ; Juan Manuel,Górriz ^[3] ; Xin,Zhang ^[4] ; Yu-Dong,Zhang ^[5]

作者单位： Department of Cardiovascular Sciences, University of Leicester, LE1 7RH, UK.;Department of Information Systems, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia.;School of Architecture Building and Civil engineering, Loughborough University, Loughborough LE11 3TU, UK. ^[1] Department of Biomedical Engineering, Kalasalingam Academy of Research and Education, Srivilliputhur post, Krishnankoil 626 126, Tamil Nadu, India. ^[2] Department of Signal Theory, Networking and Communications, University of Granada, Granada, Spain.;Department of Psychiatry, University of Cambridge, Cambridge CB21TN, UK. ^[3] Department of Medical Imaging, The Fourth People's Hospital of Huai'an, Huai'an, Jiangsu Province, 223002, China. ^[4] Department of Information Systems, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia.;School of Informatics, University of Leicester, Leicester LE1 7RH, UK. ^[5]

关键词 Batch normalization Convolutional neural network Deep feature fusion Dropout Graph convolutional network Multiple-way data augmentation Rank-based average pooling

DOI 10.1016/j.inffus.2020.10.004

PMID 33052196

发布时间 2020-12-08

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