Cargando…
A Lightweight Hierarchical Activity Recognition Framework Using Smartphone Sensors
Activity recognition for the purposes of recognizing a user's intentions using multimodal sensors is becoming a widely researched topic largely based on the prevalence of the smartphone. Previous studies have reported the difficulty in recognizing life-logs by only using a smartphone due to the...
Autores principales: | Han, Manhyung, Bang, Jae Hun, Nugent, Chris, McClean, Sally, Lee, Sungyoung |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4208169/ https://www.ncbi.nlm.nih.gov/pubmed/25184486 http://dx.doi.org/10.3390/s140916181 |
Ejemplares similares
-
Evaluation of Prompted Annotation of Activity Data Recorded from a Smart Phone
por: Cleland, Ian, et al.
Publicado: (2014) -
Behavior Life Style Analysis for Mobile Sensory Data in Cloud Computing through MapReduce
por: Hussain, Shujaat, et al.
Publicado: (2014) -
Comprehensive Context Recognizer Based on Multimodal Sensors in a Smartphone
por: Han, Manhyung, et al.
Publicado: (2012) -
Using Convolutional Neural Networks with Multiple Thermal Sensors for Unobtrusive Pose Recognition
por: Burns, Matthew, et al.
Publicado: (2020) -
A Framework for Supervising Lifestyle Diseases Using Long-Term Activity Monitoring
por: Han, Yongkoo, et al.
Publicado: (2012)