A new approach for the detection of pneumonia in children using CXR images based on an real-time IoT system.

Chagas, João Victor S das; de A Rodrigues, Douglas; Ivo, Roberto F; Hassan, Mohammad Mehedi; de Albuquerque, Victor Hugo C; Filho, Pedro P Rebouças

Chagas, João Victor S das; de A Rodrigues, Douglas; Ivo, Roberto F; Hassan, Mohammad Mehedi; de Albuquerque, Victor Hugo C; Filho, Pedro P Rebouças.

Afiliação

Chagas JVSD; Federal Institute of Education, Science and Technology of Ceará, LAPISCO, Fortaleza, CE 60040-215 Brazil.
de A Rodrigues D; Federal Institute of Education, Science and Technology of Ceará, LAPISCO, Fortaleza, CE 60040-215 Brazil.
Ivo RF; Federal Institute of Education, Science and Technology of Ceará, LAPISCO, Fortaleza, CE 60040-215 Brazil.
Hassan MM; Research Chair of Pervasive and Mobile Computing, College of Computer and Information Sciences, King Saud University, 11543 Riyadh, Saudi Arabia.
de Albuquerque VHC; Department of Computer Science, Federal Institute of Education, Science and Technology of Ceará, 60040-215 Fortaleza, CE Brazil.
Filho PPR; Department of Teleinformatics Engineering, Federal University of Ceará, 60020-181 Fortaleza, CE Brazil.

J Real Time Image Process ; 18(4): 1099-1114, 2021.

Article em En | MEDLINE | ID: mdl-33747237

Palavras-chave

Convolutional neural networks; Pneumonia detection; Real-time IoT system; Transfer learning

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Texto completo: 1 Bases de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies Idioma: En Revista: J Real Time Image Process Ano de publicação: 2021 Tipo de documento: Article

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