An Efficient and Lightweight Deep Learning Model for Human Activity Recognition Using Smartphones.

Rani, Shalli; Babbar, Himanshi; Coleman, Sonya; Singh, Aman; Aljahdali, Hani Moaiteq

Rani, Shalli; Babbar, Himanshi; Coleman, Sonya; Singh, Aman; Aljahdali, Hani Moaiteq.

Afiliação

Ankita; Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab 140401, India.
Rani S; Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab 140401, India.
Babbar H; Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab 140401, India.
Coleman S; Faculty of Computing, Ulster University Northern Ireland, Coleraine BT52 1SA, Northern Ireland, UK.
Singh A; Department of Computer Science and Engineering, Lovely Professional University, Punjab 144411, India.
Aljahdali HM; Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 37848, Saudi Arabia.

Sensors (Basel) ; 21(11)2021 Jun 02.

Article em En | MEDLINE | ID: mdl-34199559

Assuntos

Aprendizado Profundo; Algoritmos; Atividades Humanas; Humanos; Redes Neurais de Computação; Smartphone

Palavras-chave

convolutional neural network; deep learning; human activity recognition; long-short term memory

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Aprendizado Profundo Limite: Humans Idioma: En Revista: Sensors (Basel) Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Índia País de publicação: Suíça

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