Enhancing convolutional neural networks in electroencephalogram driver drowsiness detection using human inspired optimizers

Enhancing convolutional neural networks in electroencephalogram driver drowsiness detection using human inspired optimizers

Abstract Driver drowsiness is a significant safety concern, contributing to numerous traffic accidents. To address this issue, researchers have explored electroencephalogram (EEG)-based detection systems. Due to the high-dimensional nature of EEG signals and the subtle temporal patterns of drowsines...

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Bibliographic Details
Main Authors: Anupam Yadav, Rifat Hussain, Madhu Shukla, Jayaprakash B, Rishiv Kalia, S. Prince Mary, Chou-Yi Hsu, Manoj Kumar Mishra, Kashif Saleem, Mohammed El-Meligy
Format: Article
Language:English
Published: Nature Portfolio 2025-03-01
Series:Scientific Reports
Subjects:
Meta-heuristic Optimization
TLBO
SPBO
CNN
EEG
Driver Drowsiness
Online Access:https://doi.org/10.1038/s41598-025-93765-0
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