Computer Vision-Based Drowsiness Detection Using Handcrafted Feature Extraction for Edge Computing Devices

Drowsy driving contributes to over 6000 fatal incidents annually in the US, underscoring the need for effective, non-intrusive drowsiness detection. This study seeks to address detection challenges, particularly in non-standard head positions. Our innovative approach leverages computer vision by com...

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Bibliographic Details
Main Authors: Valerius Owen, Nico Surantha
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/15/2/638
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