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Simulation for a Mems-Based CTRNN Ultra-Low Power Implementation of Human Activity Recognition
This paper presents an energy-efficient classification framework that performs human activity recognition (HAR). Typically, HAR classification tasks require a computational platform that includes a processor and memory along with sensors and their interfaces, all of which consume significant power....
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Frontiers Media S.A.
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8522023/ https://www.ncbi.nlm.nih.gov/pubmed/34713201 http://dx.doi.org/10.3389/fdgth.2021.731076 |