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Classification of Physiological Signals of Fatigues using machne learning Models

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Main Author: Zainuddin, Nor Amirah
Format: Final Year Project
Published: 2024
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://utpedia.utp.edu.my/id/eprint/28603/
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id oai:utpedia.utp.edu.my:28603
record_format eprints
spelling oai:utpedia.utp.edu.my:286032024-08-08T07:32:36Z http://utpedia.utp.edu.my/id/eprint/28603/ Classification of Physiological Signals of Fatigues using machne learning Models Zainuddin, Nor Amirah TK Electrical engineering. Electronics Nuclear engineering 2024-01 Final Year Project NonPeerReviewed Zainuddin, Nor Amirah (2024) Classification of Physiological Signals of Fatigues using machne learning Models. [Final Year Project] (Submitted)
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Electronic and Digitized Intellectual Asset
url_provider http://utpedia.utp.edu.my/
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Zainuddin, Nor Amirah
Classification of Physiological Signals of Fatigues using machne learning Models
format Final Year Project
author Zainuddin, Nor Amirah
author_facet Zainuddin, Nor Amirah
author_sort Zainuddin, Nor Amirah
title Classification of Physiological Signals of Fatigues using machne learning Models
title_short Classification of Physiological Signals of Fatigues using machne learning Models
title_full Classification of Physiological Signals of Fatigues using machne learning Models
title_fullStr Classification of Physiological Signals of Fatigues using machne learning Models
title_full_unstemmed Classification of Physiological Signals of Fatigues using machne learning Models
title_sort classification of physiological signals of fatigues using machne learning models
publishDate 2024
url http://utpedia.utp.edu.my/id/eprint/28603/
_version_ 1807051972013981696
score 13.18916

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