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Enhanced Deep Learning Model for Classification of Retinal Optical Coherence Tomography Images.
Hassan, Esraa; Elmougy, Samir; Ibraheem, Mai R; Hossain, M Shamim; AlMutib, Khalid; Ghoneim, Ahmed; AlQahtani, Salman A; Talaat, Fatma M.
Afiliação
  • Hassan E; Faculty of Artificial Intelligence, Kafrelsheikh University, Kafrelsheikh 33516, Egypt.
  • Elmougy S; Department of Computer Science, Faculty of Computers and Information, Mansoura University, Mansoura 35516, Egypt.
  • Ibraheem MR; Department of Information Technology, Faculty of Computers and information, Kafrelsheikh University, Kafrelsheikh 33516, Egypt.
  • Hossain MS; Research Chair of Pervasive and Mobile Computing, Department of Software Engineering, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia.
  • AlMutib K; Department of Software Engineering, College of Computer and Information Sciences, King Saud University, Riyadh 11574, Saudi Arabia.
  • Ghoneim A; Research Chair of Pervasive and Mobile Computing, Department of Software Engineering, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia.
  • AlQahtani SA; Research Chair of Pervasive and Mobile Computing, Department of Computer Engineering, College of Computer and Information Sciences, King Saud University, Riyadh 11574, Saudi Arabia.
  • Talaat FM; Faculty of Artificial Intelligence, Kafrelsheikh University, Kafrelsheikh 33516, Egypt.
Sensors (Basel) ; 23(12)2023 Jun 07.
Article em En | MEDLINE | ID: mdl-37420558
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Redes Neurais de Computação / Aprendizado Profundo Tipo de estudo: Prognostic_studies Idioma: En Revista: Sensors (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Egito
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Redes Neurais de Computação / Aprendizado Profundo Tipo de estudo: Prognostic_studies Idioma: En Revista: Sensors (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Egito