Automated Driver Drowsiness Detection from Single-Channel EEG Signals Using Convolutional Neural Networks and Transfer Learning
Author:
Affiliation:
1. Sharif University of Technology,Department of Mechanical Engineering,Tehran,Iran
Funder
Sharif University of Technology
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9921415/9921739/09922199.pdf?arnumber=9922199
Reference30 articles.
1. An Effective Hybrid Model for EEG-Based Drowsiness Detection
2. A review on transfer learning in EEG signal analysis
3. Analysis of a sleep-dependent neuronal feedback loop: the slow-wave microcontinuity of the EEG
4. Driver Fatigue Detection with Single EEG Channel Using Transfer Learning
5. Deep Convolution Neural Network-Based Feature Learning Model for EEG Based Driver Alert/Drowsy State Detection
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1. Algorithm for drowsiness detection based on hybrid brain network parameter optimization;Biomedical Signal Processing and Control;2024-08
2. A Hybrid Deep Neural Network Approach to Recognize Driving Fatigue Based on EEG Signals;International Journal of Intelligent Systems;2024-01
3. A Hybrid Approach for Driving Behavior Recognition: Integration of CNN and Transformer-Encoder with EEG data;2023 IEEE 98th Vehicular Technology Conference (VTC2023-Fall);2023-10-10
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