Developing a Drowsiness Detection System for Safe Driving Using YOLOv9

Drowsiness detection systems play a crucial role in safe driving, considering the high rate of traffic accidents caused mainly by drowsiness. Several drowsiness detection systems built using the eye aspect ratio (EAR), percentage of eyelid closure (PERCLOS), and convolutional neural network (CNN) me...

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Bibliographic Details
Main Authors: Fernando Candra Yulianto, Wiwit Agus Triyanto, Syafiul Muzid
Format: Article
Language:English
Published: Universitas Gadjah Mada 2025-05-01
Series:Jurnal Nasional Teknik Elektro dan Teknologi Informasi
Subjects:
Online Access:https://jurnal.ugm.ac.id/v3/JNTETI/article/view/18701
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