An optimal cascaded recurrent neural network for intelligent COVID-19 detection using chest x-ray images

dc.contributor.author	Shankar, K.
dc.contributor.author	Perumal, E.
dc.contributor.author	García Díaz, Vicente
dc.contributor.author	Tiwari, P.
dc.contributor.author	Gupta, D.
dc.contributor.author	Saudagar, A. K. J.
dc.contributor.author	Muhammad, K.
dc.date.accessioned	2022-03-11T07:30:31Z
dc.date.available	2022-03-11T07:30:31Z
dc.date.issued	2021
dc.identifier.citation	Applied soft computing, 113 (2021); doi:10.1016/j.asoc.2021.107878
dc.identifier.issn	1568-4946
dc.identifier.uri	http://hdl.handle.net/10651/62310
dc.description.sponsorship	The authors extend their appreciation to the Deputyship for Research & Innovation, Ministry of Education in Saudi Arabia for funding this research work through the project number 959.
dc.language.iso	eng
dc.relation.ispartof	Applied soft computing
dc.rights	© 2021 Elsevier B.V. All rights reserved.
dc.source	Scopus
dc.source.uri	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85115254209&doi=10.1016%2fj.asoc.2021.107878&partnerID=40&md5=6f8d85c903527d974e9c67e90060f936
dc.title	An optimal cascaded recurrent neural network for intelligent COVID-19 detection using chest x-ray images
dc.type	journal article
dc.identifier.doi	10.1016/j.asoc.2021.107878
dc.relation.publisherversion	http://dx.doi.org/10.1016/j.asoc.2021.107878

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