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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...
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| Publicat a: | Sensors (Basel) |
|---|---|
| Autors principals: | , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
MDPI
2019
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6749525/ https://ncbi.nlm.nih.gov/pubmed/31450654 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/s19173688 |
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