DeiT Model for Iranian Traffic Sign Recognition in Advanced Driver Assistance Systems

Abstract

چکیده Due to the important relationship of the impact of accurate detection of traffic signs in self-driving cars and driver assistance during car movement, it is very challenging and necessary to create a high-accuracy system for interpretation and immediate decision-making. In this research, by applying the new vision transformer DeiT approach, a system is designed that can recognize Iranian traffic signs. we trained our model with a two collections of traffic signs images (GTSRB, PTSD) that reaches a higher accuracy of 99.5% and 98.8% respectively in optimal conditions. کلیدواژه ها