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Activity Recognition on Subject Independent Using Machine Learning Cover

Activity Recognition on Subject Independent Using Machine Learning

Cybernetics and Information Technologies
Volume 20 (2020): Issue 3 (September 2020)
By: Y. J. Kee,  M. N. Shah Zainudin,  M. I. Idris,  R. H. Ramlee and  M. R. Kamarudin  
Open Access
|Sep 2020

Authors

Y. J. Kee

jkyong96@gmail.com

Cetri, Faculty of Electronics and Computer Engineering, University Teknikal Malaysia Melaka, Malaysia

M. N. Shah Zainudin

noorazlan@utem.edu.my

Cetri, Faculty of Electronics and Computer Engineering, University Teknikal Malaysia Melaka, Malaysia

M. I. Idris

idzdihar@utem.edu.my

Cetri, Faculty of Electronics and Computer Engineering, University Teknikal Malaysia Melaka, Malaysia

R. H. Ramlee

radihusin@utem.edu.my

Cetri, Faculty of Electronics and Computer Engineering, University Teknikal Malaysia Melaka, Malaysia

M. R. Kamarudin

raihaan@utem.edu.my

Cetri, Faculty of Electronics and Computer Engineering, University Teknikal Malaysia Melaka, Malaysia
DOI: https://doi.org/10.2478/cait-2020-0028 | Journal eISSN: 1314-4081 | Journal ISSN: 1311-9702
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Language: English
Page range: 64 - 74
Submitted on: Mar 26, 2020
|
Accepted on: Jul 27, 2020
|
Published on: Sep 13, 2020
Published by: Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
Activity Daily Living (ADL),
accelerometer,
wearable sensor,
machine learning
Related subjects:
Computer sciences,
Information technology

© 2020 Y. J. Kee, M. N. Shah Zainudin, M. I. Idris, R. H. Ramlee, M. R. Kamarudin, published by Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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