Real-time-Driver-Drowsiness-Detection-System-Using-Deep-Learning and Driver-Drowsiness-Detection
These two projects are competitors, as both aim to provide a real-time driver drowsiness detection system using deep learning, offering alternative implementations for the same core task.
About Real-time-Driver-Drowsiness-Detection-System-Using-Deep-Learning
Pratham-mehta/Real-time-Driver-Drowsiness-Detection-System-Using-Deep-Learning
CS-GY 6953 Deep Learning Major Project
This system helps prevent road accidents by detecting driver drowsiness in real-time. It takes live video footage of a driver's face as input and outputs an alert when signs of drowsiness, like closed eyes or yawning, are detected. This tool is designed for anyone who operates a vehicle, especially professional drivers or individuals embarking on long journeys.
About Driver-Drowsiness-Detection
DivitMittal/Driver-Drowsiness-Detection
Real-time drowsiness detection on driver's face continuously for signs of fatigue using deep learning methodologies
This system helps monitor a driver's face in real-time using a camera to detect signs of fatigue. It takes a continuous video feed of the driver's face and outputs alerts if drowsiness is detected, based on eye closures, head movements, and yawning. Trucking companies, fleet managers, and anyone responsible for driver safety can use this to prevent accidents.
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