Drawsiness Detection for Enhanced Surveillance and Safety: A Deep Learning approach
Abstract This project delves into the development of a robust drowsiness detection system leveraging deep learning methodologies. Beginning with the collection of open and closed eye data, the project progresses through meticulous image preprocessing and training of Convolutional Neural Networks (CNNs) and residual networks. Through fine-tuning and rigorous evaluation, a superior model is crafted, poised…