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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...
Autores principales: | Bento, Nuno, Rebelo, Joana, Barandas, Marília, Carreiro, André V., Campagner, Andrea, Cabitza, Federico, Gamboa, Hugo |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
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 |
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