A novel perceptual two layer image fusion using deep learning for imbalanced COVID-19 dataset.

Elzeki, Omar M; Abd Elfattah, Mohamed; Salem, Hanaa; Hassanien, Aboul Ella; Shams, Mahmoud

Elzeki, Omar M; Abd Elfattah, Mohamed; Salem, Hanaa; Hassanien, Aboul Ella; Shams, Mahmoud.

Afiliação

Elzeki OM; Faculty of Computers and Information Sciences, Mansoura University, Mansoura, Egypt.
Abd Elfattah M; Misr Higher Institute for Commerce and Computers, Mansoura, Egypt.
Salem H; Communications and Computers Engineering Department, Faculty of Engineering, Delta University for Science and Technology, Gamasa, Egypt.
Hassanien AE; Faculty of Computers and Artificial Intelligence, Cairo University, Cairo, Egypt.
Shams M; Scientific Research Group in Egypt (SRGE), Cairo, Egypt.

PeerJ Comput Sci ; 7: e364, 2021.

Article em En | MEDLINE | ID: mdl-33817014

Palavras-chave

CNN; COVID19; Coronavirus; Deep learning; Feature analysis; Feature extraction; Image fusion; Machine learning; NSCT; VGG19

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: PeerJ Comput Sci Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Egito

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