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

Convolutional neural networks (CNNs) have demonstrated exceptional results in the analysis of time- series data when used for Human Activity Recognition (HAR). The manual design of such neural architectures is an error-prone and time-consuming process. The search for optimal CNN architectures is con...

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Detalles Bibliográficos
Autores principales: Ismail, Walaa N., Alsalamah, Hessah A., Hassan, Mohammad Mehedi, Mohamed, Ebtesam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Review Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9958436/
https://www.ncbi.nlm.nih.gov/pubmed/36852018
http://dx.doi.org/10.1016/j.heliyon.2023.e13636

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9958436/
https://www.ncbi.nlm.nih.gov/pubmed/36852018
http://dx.doi.org/10.1016/j.heliyon.2023.e13636

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