COVID-AleXception: A Deep Learning Model Based on a Deep Feature Concatenation Approach for the Detection of COVID-19 from Chest X-ray Images.

Ayadi, Manel; Ksibi, Amel; Al-Rasheed, Amal; Soufiene, Ben Othman

Ayadi, Manel; Ksibi, Amel; Al-Rasheed, Amal; Soufiene, Ben Othman.

Afiliación

Ayadi M; Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia.
Ksibi A; Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia.
Al-Rasheed A; Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia.
Soufiene BO; Prince Laboratory Research, ISITcom (Institut Supérieur d'Informatique et des Techniques de Communication de Hammam Sousse), University of Sousse, Hammam Sousse 4023, Tunisia.

Healthcare (Basel) ; 10(10)2022 Oct 18.

Article en En | MEDLINE | ID: mdl-36292519

Palabras clave

AlexNet; COVID-19; COVID-AlexCeption; Xception; chest X-ray images; deep feature concatenation; deep learning

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Healthcare (Basel) Año: 2022 Tipo del documento: Article País de afiliación: Arabia Saudita

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