Activity Graph Feature Selection for Activity Pattern Classification
Sensor-based activity recognition is attracting growing attention in many applications. Several studies have been performed to analyze activity patterns from an activity database gathered by activity recognition. Activity pattern classification is a technique that predicts class labels of people suc...
Saved in:
Main Authors: | Kisung Park, Yongkoo Han, Young-Koo Lee |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2014-04-01
|
Series: | International Journal of Distributed Sensor Networks |
Online Access: | https://doi.org/10.1155/2014/254256 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Human Activity Recognition Based on the Hierarchical Feature Selection and Classification Framework
by: Yuhuang Zheng
Published: (2015-01-01) -
Feature Selection with Graph Mining Technology
by: Thosini Bamunu Mudiyanselage, et al.
Published: (2019-06-01) -
Memristor-based feature learning for pattern classification
by: Tuo Shi, et al.
Published: (2025-01-01) -
An Improved Feature Selection Based on Effective Range for Classification
by: Jianzhong Wang, et al.
Published: (2014-01-01) -
NF-GAT: A Node Feature-Based Graph Attention Network for ASD Classification
by: Shuaiqi Liu, et al.
Published: (2024-01-01)