HSTCN-NuSVC: A Homogeneous Stacked Deep Ensemble Learner for Classifying Human Actions Using Smartphones

HSTCN-NuSVC: A Homogeneous Stacked Deep Ensemble Learner for Classifying Human Actions Using Smartphones

Smartphone-based human activity recognition (HAR) is an important research area due to its wide-ranging applications in health, security, gaming, etc. Existing HAR models face challenges such as tedious manual feature extraction/selection techniques, limited model generalisation, high computational...

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Bibliographic Details
Main Authors:	Sarmela Raja Sekaran, Ying Han Pang, Ooi Shih Yin, Lim Zheng You
Format:	Article
Language:	English
Published:	Ital Publication 2025-02-01
Series:	Emerging Science Journal
Subjects:	deep ensemble learning smartphone-based human activity recognition stacking ensemble lightweight model hierarchical deep features.
Online Access:	https://ijournalse.org/index.php/ESJ/article/view/2571
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