利用深度神经网络实时检测驾驶员瞌睡情况

International Integrated Intelligent Systems Pub Date : 2024-06-01 DOI:10.21608/iiis.2024.357785

Daniel Halim, Mariam Hanafy, Youssef Lotfy, Mohanad Deif, Rania Elgohary

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摘要

-摘要：本文提出了一种基于眼球弧度的司机瞌睡检测方法，用于预防事故。我们的尝试是开发一种深度学习模型，通过提取眼睛来实时使用摄像头的输入，从而检测司机的嗜睡程度。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Real-time Driver Drowsiness Detection Using Deep Neural Networks

—Abstract: This paper presents a driver drowsiness detection for accident prevention which is based on the curvature of the eye. Our attempt is to develop a deep learning model that can use the input from a camera in real time by extracting the eyes to detect the drowsiness of the drivers.This paper helps to resolve the problem of drowsiness detection with an accuracy of 96% for test and 99% for validation

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International Integrated Intelligent Systems

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