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In Shift and In Variance: Assessing the Robustness of HAR Deep Learning Models against Variability

Fuente: arXiv

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Detalles Bibliográficos
Autores principales:	Khaked, Azhar Ali, Oishi, Nobuyuki, Roggen, Daniel, Lago, Paula
Formato:	Preprint
Publicado:	2025
Materias:	Human-Computer Interaction Machine Learning Signal Processing
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

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