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An Energy-Efficient Method for Human Activity Recognition with Segment-Level Change Detection and Deep Learning
Human activity recognition (HAR), which is important in context awareness services, needs to occur continuously in daily life, owing to which an energy-efficient method is needed. However, because human activities have a longer cycle than HAR methods, which have analysis cycles of a few seconds, con...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2019
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6749525/ https://www.ncbi.nlm.nih.gov/pubmed/31450654 http://dx.doi.org/10.3390/s19173688 |