Enhancing Driver Safety: Real-Time Drowsiness Detection through Eye Aspect Ratio and CNN-Based Eye State Analysis
Author:
Affiliation:
1. Vellore Institute of Technology,Department of Analytics,Tamil Nadu,India
2. Vellore Institute of Technology,Department of IoT,Tamil Nadu,India
3. Vellore Institute of Technology,School of Computer Science and Engineering,Tamil Nadu,India
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10467176/10467219/10467769.pdf?arnumber=10467769
Reference10 articles.
1. Real-time monitoring of driver drowsiness on mobile platforms using 3D neural networks
2. Driver drowsiness detection using hybrid convolutional neural network and long short-term memory
3. Real-Time System for Driver Fatigue Detection Based on a Recurrent Neuronal Network
4. Driver Fatigue Detection Based on Convolutional Neural Networks Using EM-CNN
5. An Effective Hybrid Model for EEG-Based Drowsiness Detection
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