BRAINPRINT AUTHENTICATION UNDER VARYING ENVIRONMENTAL CONDITIONS: MACHINE LEARNING VERSUS DEEP LEARNING

This study explores the potential of using EEG signals for biometric authentication through the development of Convolutional Neural Network (CNN) model. In particular, the electroencephalogram (EEG) signals were recorded in different ambient noise settings: quiet environment, low-distraction envir...

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Bibliographic Details

Main Authors:	DARIEN, KEEGAN, Liew, Siaw Hong, Tang, SIEW YIN, Choo, Yun Huoy, Stephanie, Chua, SOON, CHONG CHEE
Format:	Article
Language:	en
Published:	SCIK Publishing Corporation 2026
Subjects:	QA75 Electronic computers. Computer science
Online Access:	http://ir.unimas.my/id/eprint/51579/1/9617-21134-1-PB.pdf http://ir.unimas.my/id/eprint/51579/ https://scik.org/index.php/cmbn/article/view/9617 https://doi.org/10.28919/cmbn/9617
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