Deep Learning Approach for COVID-19 Detection: A Diagnostic Tool Based on VGG16 and VGG19

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dc.contributor.authorAkash, Fardin Rahman
dc.contributor.authorPriniya, Ajmiri Afrin
dc.contributor.authorChadni, Jahani Shabnam
dc.contributor.authorShuha, Jobaida Ahmed
dc.contributor.authorEmu, Ismot Ara
dc.contributor.authorReza, Ahmed Wasif
dc.contributor.authorArefin, Mohammad Shamsul
dc.date.accessioned2024-05-11T10:10:41Z
dc.date.available2024-05-11T10:10:41Z
dc.date.issued2020-12-20
dc.description.abstractThe coronavirus disease 2019 is a new contagious illness affecting the lungs and upper respiratory tract. It has various complications that can affect the quality of life. One of the most common factors that can be used to diagnose this illness is chest computed radiography. According to studies, deep learning can identify COVID-19 using chest radiography results. We created a CNN network to find COVID-19 in patients with Pneumonia and normal controls after a full chest X-ray. For the testing and training of the VGG16 model, we focused on its deep features. The study's results revealed that the VGG16 model had the highest accuracy score, at 70.0021%.
dc.identifier.otherhttp://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/12331
dc.identifier.urihttp://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/12331
dc.language.isoen_US
dc.publisherSpringer
dc.sourceDIU Institutional Repository
dc.subjectCoronavirus disease
dc.subjectCovid-19
dc.subjectVaccination
dc.subjectDeep learning
dc.titleDeep Learning Approach for COVID-19 Detection: A Diagnostic Tool Based on VGG16 and VGG19
dc.typeArticle

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