Random subspace K-NN based ensemble classifier for driver fatigue detection utilizing selected EEG channels

Random subspace K-NN based ensemble classifier for driver fatigue detection utilizing selected EEG channels

Nowadays, many studies have been conducted to assess driver fatigue, as it has become one of the leading causes of traffic crashes. However, with the use of advanced features and machine learning approaches, EEG signals may be processed in an effective way, allowing fatigue to be detected promptly a...

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Bibliographic Details
Main Authors: Rashid, Mamunur, Mahfuzah, Mustafa, Norizam, Sulaiman, Nor Rul Hasma, Abdullah, Rosdiyana, Samad
Format: Article
Language:English
Published: International Information and Engineering Technology Association 2021
Subjects:
T Technology (General)
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://umpir.ump.edu.my/id/eprint/33117/1/Random%20subspace%20K-NN%20based%20ensemble%20classifier%20for%20driver%20fatigue%20detection%20utilizing%20selected%20EEG%20channels.pdf

Internet

http://umpir.ump.edu.my/id/eprint/33117/1/Random%20subspace%20K-NN%20based%20ensemble%20classifier%20for%20driver%20fatigue%20detection%20utilizing%20selected%20EEG%20channels.pdf

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