Improved Spatiotemporal Framework for Human Activity Recognition in Smart Environment

The rapid development of microsystems technology with the availability of various machine learning algorithms facilitates human activity recognition (HAR) and localization by low-cost and low-complexity systems in various applications related to industry 4.0, healthcare, ambient assisted living as w...

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Detalles Bibliográficos
Autores principales: Salem, Ziad, Weiss, Andreas Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9824688/
https://www.ncbi.nlm.nih.gov/pubmed/36616729
http://dx.doi.org/10.3390/s23010132

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9824688/
https://www.ncbi.nlm.nih.gov/pubmed/36616729
http://dx.doi.org/10.3390/s23010132

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