AUTO-HAR: An adaptive human activity recognition framework using an automated CNN architecture design.

Ismail, Walaa N; Alsalamah, Hessah A; Hassan, Mohammad Mehedi; Mohamed, Ebtesam

Ismail, Walaa N; Alsalamah, Hessah A; Hassan, Mohammad Mehedi; Mohamed, Ebtesam.

Afiliação

Ismail WN; Department of Management Information Systems, College of Business Administration, Al Yamamah University, 11512, Riyadh, Saudi Arabia.
Alsalamah HA; Faculty of Computers and Information, Minia University, 61519, Minia, Egypt.
Hassan MM; Information Systems Department, College of Computer and Information Sciences, King Saud University, 4545, Riyadh, Saudi Arabia.
Mohamed E; Computer Engineering Department, College of Engineering and Architecturen, Al Yamamah University, 11512, Riyadh, Saudi Arabia.

Heliyon ; 9(2): e13636, 2023 Feb.

Article em En | MEDLINE | ID: mdl-36852018

Palavras-chave

CNN topology; Convolution neural networks; Deep learning; Evolutionary neural network search; Genetic algorithms; Human activity recognition

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Texto completo: 1 Bases de dados: MEDLINE Idioma: En Revista: Heliyon Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Arábia Saudita