Combining Supervised and Unsupervised Learning Algorithms for Human Activity Recognition

Human activity recognition is an extensively researched topic in the last decade. Recent methods employ supervised and unsupervised deep learning techniques in which spatial and temporal dependency is modeled. This paper proposes a novel approach for human activity recognition using skeleton data. T...

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Detalles Bibliográficos
Autores principales: Budisteanu, Elena-Alexandra, Mocanu, Irina Georgiana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8473063/
https://www.ncbi.nlm.nih.gov/pubmed/34577515
http://dx.doi.org/10.3390/s21186309

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8473063/
https://www.ncbi.nlm.nih.gov/pubmed/34577515
http://dx.doi.org/10.3390/s21186309

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