Efficient Human Gait Activity Recognition Based on Sensor Fusion and Intelligent Stacking Framework-Reference-Cited by-同舟云学术

Efficient Human Gait Activity Recognition Based on Sensor Fusion and Intelligent Stacking Framework

Published:2023-11-15 Issue:22 Volume:23 Page:28355-28369
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Tarekegn Adane Nega¹^ORCID,Sajjad Muhammad¹,Cheikh Faouzi Alaya¹^ORCID,Ullah Mohib¹^ORCID,Muhammad Khan²^ORCID

Affiliation:

1. Department of Computer Science, Norwegian University of Science and Technology, Gjøvik, Norwa

2. Department of Applied Artificial Intelligence, School of Convergence, College of Computing and Informatics, Visual Analytics for Knowledge Laboratory, Sungkyunkwan University, Seoul, Republic of Korea

Funder

European Union through the Horizon 2020 Research and Innovation Programme

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/7361/10316685/10268889.pdf?arnumber=10268889

Reference52 articles.

1. Predictive Modeling for Frailty Conditions in Elderly People: Machine Learning Approaches

2. MMHAR-EnsemNet: A Multi-Modal Human Activity Recognition Model

3. LSTM Networks Using Smartphone Data for Sensor-Based Human Activity Recognition in Smart Homes

4. Deep Recurrent Neural Networks for Human Activity Recognition

5. Comparing Human Activity Recognition Models Based on Complexity and Resource Usage

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