A deep transfer learning-based convolution neural network model for COVID-19 detection using computed tomography scan images for medical applications.

Kathamuthu, Nirmala Devi; Subramaniam, Shanthi; Le, Quynh Hoang; Muthusamy, Suresh; Panchal, Hitesh; Sundararajan, Suma Christal Mary; Alrubaie, Ali Jawad; Zahra, Musaddak Maher Abdul

Kathamuthu, Nirmala Devi; Subramaniam, Shanthi; Le, Quynh Hoang; Muthusamy, Suresh; Panchal, Hitesh; Sundararajan, Suma Christal Mary; Alrubaie, Ali Jawad; Zahra, Musaddak Maher Abdul.

Affiliation

Kathamuthu ND; Department of Computer Science and Engineering, Kongu Engineering College (Autonomous), Perundurai, Erode, Tamil Nadu, India.
Subramaniam S; Department of Computer Science and Engineering, Kongu Engineering College (Autonomous), Perundurai, Erode, Tamil Nadu, India.
Le QH; Institute of Research and Development, Duy Tan University, Da Nang, Vietnam.
Muthusamy S; School of Medicine and Pharmacy, Duy Tan University, Da Nang, Vietnam.
Panchal H; Department of Electronics and Communication Engineering, Kongu Engineering College (Autonomous), Perundurai, Erode, Tamil Nadu, India.
Sundararajan SCM; Department of Mechanical Engineering, Government Engineering College, Patan, Gujarat, India.
Alrubaie AJ; Department of Information Technology, Panimalar Engineering College (Autonomous), Poonamallee, Chennai, Tamil Nadu, India.
Zahra MMA; Department of Medical Instrumentation Techniques Engineering, Al- Mustaqbal University College, 51001, Hilla, Iraq.

Adv Eng Softw ; 175: 103317, 2023 Jan.

Article de En | MEDLINE | ID: mdl-36311489

Mots clés

CNN; COVID-19; Deep learning; DenseNet121; InceptionV3; ResNet-50; Transfer learning; VGG16; VGG19

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Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Type d'étude: Diagnostic_studies / Prognostic_studies / Screening_studies Langue: En Journal: Adv Eng Softw Année: 2023 Type de document: Article Pays d'affiliation: Inde Pays de publication: Royaume-Uni

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