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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Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
Universitas Gadjah Mada
2025-05-01
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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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