[PDF][PDF] A CNN-LSTM-based deep learning approach for driver drowsiness prediction
MW Gomaa, RO Mahmoud… - Journal of Engineering …, 2022 - erjeng.journals.ekb.eg
The development of neural networks and machine learning techniques has recently been
the cornerstone for many applications of artificial intelligence. These applications are now …
the cornerstone for many applications of artificial intelligence. These applications are now …
FMIF: facial multi-feature information fusion for driver fatigue detection
Driver fatigue is a major contributing factor to traffic accidents, and accurately detecting
driver fatigue is crucial. Existing methods for driver fatigue detection face limitations in …
driver fatigue is crucial. Existing methods for driver fatigue detection face limitations in …
Driver Drowsiness Detection using MobileNetV2 with Transfer Learning Approach
S Pahariya, P Vats, S Suchitra - 2024 International Conference …, 2024 - ieeexplore.ieee.org
Drowsiness among drivers is one of the leading causes of road accidents and deaths. In this
research, we propose a new way to detect driver drowsiness using MobileNet architecture …
research, we propose a new way to detect driver drowsiness using MobileNet architecture …