An Elderly Fall Detection System Using Enhanced Random Forest in Machine Learning-Reference-Cited by-同舟云学术

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An Elderly Fall Detection System Using Enhanced Random Forest in Machine Learning

Published:2024-01-16 Issue: Volume:7 Page:172
ISSN:
Container-title:RAiSE-2023
language:
Short-container-title:

Author:

Subburam Ravikumar¹^ORCID,Chandralekha Ethirajulu¹,Kandasamy Vijay²^ORCID

Affiliation:

1. Department of Computer Science & Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Avadi, Chennai 600062, India

2. Department of Computer Science and Engineering, Rajalakshmi Engineering College, Chennai 602105, India

Publisher

MDPI

Link

https://www.mdpi.com/2673-4591/59/1/172/pdf

Reference20 articles.

1. Fall detection for elderly people using the variation of key points of human skeleton;Alaoui;IEEE Access,2019

2. Alaoui, A.Y., Tabii, Y., Thami, R.O.H., Daoudi, M., Berretti, S., and Pala, P. (2021). Fall detection of elderly people using the manifold of positive semidefinite matrices. J. Imaging, 7.

3. Amara, M.I., Akkouche, A., Boutellaa, E., and Tayakout, H. (2021, January 9–10). A smartphone application for fall detection using accelerometer and convlstm network. Proceedings of the 2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH), Boumerdes, Algeria.

4. Deep learning for vision-based fall detection system: Enhanced optical dynamic flow;Chhetri;Comput. Intell.,2021

5. Deep learning-based near-fall detection algorithm for fall risk monitoring system using a single inertial measurement unit;Choi;IEEE Trans. Neural Syst. Rehabil. Eng.,2022

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