A survey on visual and non-visual features in Driver's drowsiness detection

NN Pandey, NB Muppalaneni - Multimedia Tools and Applications, 2022 - Springer
Many road accidents are happening due to the negligent behaviour of the drivers, which
increases the death rate day by day. The tiredness and drowsiness of the drivers are the …

Event-based driver distraction detection and action recognition

C Yang, P Liu, G Chen, Z Liu, Y Wu… - 2022 IEEE International …, 2022 - ieeexplore.ieee.org
Driver distraction is one of the important factors leading to traffic accidents. With the
development of mobile infotainment and the overestimation of immature autonomous driving …

[PDF][PDF] Neural network model for recognition and classification of types of interactions in road traffic

S Efremov, T Kochetova - Transactions on transport sciences, 2022 - tots.upol.cz
The article presents neural network for recognition of driving strategies based on
interactions between drivers in road traffic. It analyzes the architecture of the model …

A Study on Accident Detection Systems Using Machine Learning

S Savitha, N Sreedevi - … Conference on Innovations in Computer Science …, 2022 - Springer
Safety is the top priority of every individual in our day to day lives. Urbanization as led to a
rise in the trend of motorization which as influenced the road safety measures directly or …

Drowsiness and Yawn Detection System using Machine Learning

S Shukla, VK Sharma - Mathematical Statistician and Engineering …, 2022 - philstat.org
Face produce data that can be used to determine tiredness level. Many facial appearances
derived from the face to decide the extent of fatigue. Yawning, head movements and eye …

[引用][C] Drowsiness Detection of Driver using Novel Random Forest Classifier and Logistic Regression Classifier with Improved Accuracy

D Nikitha, S Kalaiarasi - Baltic Journal of Law & Politics, 2022