Implementation of CNN based COVID-19 classification model from CT images

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dc.authoridATAŞ, Kubilay/0000-0002-3307-866X
dc.authoridMyderrizi, Indrit/0000-0002-2112-7911
dc.contributor.authorKaya, Atakan
dc.contributor.authorAtas, Kubilay
dc.contributor.authorMyderrizi, Indrit
dc.date.accessioned2024-09-11T19:51:57Z
dc.date.available2024-09-11T19:51:57Z
dc.date.issued2021
dc.departmentİstanbul Gelişim Üniversitesien_US
dc.description19th IEEE World Symposium on Applied Machine Intelligence and Informatics (SAMI) -- JAN 21-23, 2021 -- SLOVAKIAen_US
dc.description.abstractThe number of COVID-19 patients around the globe is increasing day by day. Statistics show that even after almost 10 months from outbreak, number of the total patients has not reached to its peak value yet. Easy spreading of the virus among people causes high number of patients at the same time. Accelerating the reduction in spread is of vital importance. In order to achieve this reduction, early diagnosis of the disease and the number of tests and scans to be performed frequently becomes important. In this paper, a comprehensive model examination is made to overcome COVID-19 diagnosing problem. Using CT images, data augmentation technique is applied first in the pre-processing section and then pre-trained deep CNN networks perform the classification. The model is tested using various networks and high accuracy results of 96.5% and 97.9% are obtained for VGG-16 and EfficientNetB3 networks, respectively.en_US
dc.description.sponsorshipIEEE,Tech Univ Kosice,Obuda Univ, Univ Res & Innovat Ctr,Obuda Univ, Antal Bejczy Ctr Intelligent Robot,Elfa Ltd,Slovak Acad Sci,SMC TC Computat Cybernet,IEEE Czechoslovak Sect, Computat Intelligence Chapter,IEEE Hungary Sect,IEEE Joint Chapter IES & RAS,IEEE Control Syst Chapter,IEEE SMC Chapter,IEEE SMC Socen_US
dc.identifier.doi10.1109/SAMI50585.2021.9378646
dc.identifier.endpage206en_US
dc.identifier.isbn978-1-7281-8053-3
dc.identifier.scopus2-s2.0-85103816514en_US
dc.identifier.startpage201en_US
dc.identifier.urihttps://doi.org/10.1109/SAMI50585.2021.9378646
dc.identifier.urihttps://hdl.handle.net/11363/7873
dc.identifier.wosWOS:000671855400034en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartof2021 Ieee 19th World Symposium on Applied Machine Intelligence And Informatics (Sami 2021)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.snmz20240903_Gen_US
dc.subjectCovid-19en_US
dc.subjectDeep Learningen_US
dc.subjectClassificationen_US
dc.subjectComputed Tomographyen_US
dc.titleImplementation of CNN based COVID-19 classification model from CT imagesen_US
dc.typeConference Objecten_US

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