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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Detalhes bibliográficos
Principais autores: Rashid, Mamunur, Mahfuzah, Mustafa, Norizam, Sulaiman, Nor Rul Hasma, Abdullah, Rosdiyana, Samad
Formato: Artigo
Idioma:English
Publicado em: International Information and Engineering Technology Association 2021
Assuntos:
T Technology (General)
TK Electrical engineering. Electronics Nuclear engineering
Acesso em linha: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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