Cargando…
Towards Human Activity Recognition: A Hierarchical Feature Selection Framework
The inherent complexity of human physical activities makes it difficult to accurately recognize activities with wearable sensors. To this end, this paper proposes a hierarchical activity recognition framework and two different feature selection methods to improve the recognition performance. Specifi...
Autores principales: | Wang, Aiguo, Chen, Guilin, Wu, Xi, Liu, Li, An, Ning, Chang, Chih-Yung |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6263870/ https://www.ncbi.nlm.nih.gov/pubmed/30366461 http://dx.doi.org/10.3390/s18113629 |
Ejemplares similares
-
Towards a Clustering Guided Hierarchical Framework for Sensor-Based Activity Recognition
por: Wang, Aiguo, et al.
Publicado: (2021) -
A Lightweight Hierarchical Activity Recognition Framework Using Smartphone Sensors
por: Han, Manhyung, et al.
Publicado: (2014) -
A Hierarchical Feature and Sample Selection Framework and Its Application for Alzheimer’s Disease Diagnosis
por: An, Le, et al.
Publicado: (2017) -
Anatomical Entity Recognition with a Hierarchical Framework Augmented by External Resources
por: Xu, Yan, et al.
Publicado: (2014) -
Harvestman: a framework for hierarchical feature learning and selection from whole genome sequencing data
por: Frisby, Trevor S., et al.
Publicado: (2021)