Counting Activities Using Weakly Labeled Raw Acceleration Data: A Variable-Length Sequence Approach with Deep Learning to Maintain Event Duration Flexibility

This paper presents a novel approach for counting hand-performed activities using deep learning and inertial measurement units (IMUs). The particular challenge in this task is finding the correct window size for capturing activities with different durations. Traditionally, fixed window sizes have be...

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Detalles Bibliográficos
Autores principales: Sopidis, Georgios, Haslgrübler, Michael, Ferscha, Alois
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10255870/
https://www.ncbi.nlm.nih.gov/pubmed/37299784
http://dx.doi.org/10.3390/s23115057

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10255870/
https://www.ncbi.nlm.nih.gov/pubmed/37299784
http://dx.doi.org/10.3390/s23115057

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