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Title: DRIVER DROWSINESS DETECTION SYSTEM BY REAL TIME EYE STATE IDENTIFICATION
Authors: Hajra Asif, Dr. Ghulam Mustafa
Journal: Spectrum of Engineering Sciences
| Category | From | To |
|---|---|---|
| Y | 2024-10-01 | 2025-12-31 |
Publisher: Sociology Educational Nexus Research Institute
Country: Pakistan
Year: 2025
Volume: 3
Issue: 8
Language: en
Keywords: Deep learningRNNLSTMCNNReal-time monitoringRoad SafetyDriver monitoring systemDriver Drowsiness DetectionSmart Vehicle SystemsEye State IdentificationBehavioral Analysis
The paper proposes a new architecture which plies eye states of a live video feed and receives at 97 percent accuracy; followed by sending signals at the right time before instances of accidents occur and this is an immense problem in the globe since traffic accidents by fatigued drivers are a huge menace. It is a combined CNN and RNN based system. A comprehensive dataset of 4,760 images, comprising 2,380 closed-eye and 2,380 open-eye images captured under diverse driving conditions, is used to train the model.
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