A Novel Energy-Efficient Approach for Human Activity Recognition

In this paper, we propose a novel energy-efficient approach for mobile activity recognition system (ARS) to detect human activities. The proposed energy-efficient ARS, using low sampling rates, can achieve high recognition accuracy and low energy consumption. A novel classifier that integrates hiera...

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Detalles Bibliográficos
Autores principales: Zheng, Lingxiang, Wu, Dihong, Ruan, Xiaoyang, Weng, Shaolin, Peng, Ao, Tang, Biyu, Lu, Hai, Shi, Haibin, Zheng, Huiru
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5621091/
https://www.ncbi.nlm.nih.gov/pubmed/28885560
http://dx.doi.org/10.3390/s17092064

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5621091/
https://www.ncbi.nlm.nih.gov/pubmed/28885560
http://dx.doi.org/10.3390/s17092064

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