Hybrid classification structures for automatic COVID-19 detection.

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Bibliographic Details
Title: Hybrid classification structures for automatic COVID-19 detection.
Authors: Shoaib MR; Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, 32952 Egypt., Emara HM; Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, 32952 Egypt., Elwekeil M; Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, 32952 Egypt.; Department of Electrical and Information Engineering, University of Cassino and Southern Lazio, Cassino, Italy., El-Shafai W; Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, 32952 Egypt.; Security Engineering Lab, Computer Science Department, Prince Sultan University, Riyadh, 11586 Saudi Arabia., Taha TE; Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, 32952 Egypt., El-Fishawy AS; Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, 32952 Egypt., El-Rabaie EM; Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, 32952 Egypt., El-Samie FEA; Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, 32952 Egypt.; Department of Information Technology, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia.
Source: Journal of ambient intelligence and humanized computing [J Ambient Intell Humaniz Comput] 2022; Vol. 13 (9), pp. 4477-4492. Date of Electronic Publication: 2022 Mar 07.
Publication Type: Journal Article
Journal Info: Publisher: Springer Country of Publication: Germany NLM ID: 101538212 Publication Model: Print-Electronic Cited Medium: Print ISSN: 1868-5137 (Print) NLM ISO Abbreviation: J Ambient Intell Humaniz Comput Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1868-5137
DOI:10.1007/s12652-021-03686-9