Comparing Handcrafted Features and Deep Neural Representations for Domain Generalization in Human Activity Recognition

Human Activity Recognition (HAR) has been studied extensively, yet current approaches are not capable of generalizing across different domains (i.e., subjects, devices, or datasets) with acceptable performance. This lack of generalization hinders the applicability of these models in real-world envir...

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Detalles Bibliográficos
Autores principales: Bento, Nuno, Rebelo, Joana, Barandas, Marília, Carreiro, André V., Campagner, Andrea, Cabitza, Federico, Gamboa, Hugo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9572241/
https://www.ncbi.nlm.nih.gov/pubmed/36236427
http://dx.doi.org/10.3390/s22197324

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9572241/
https://www.ncbi.nlm.nih.gov/pubmed/36236427
http://dx.doi.org/10.3390/s22197324

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