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

نویسندگانMarjan Shahchera
همایشThe 6th International Conference on Pattern Recognition and Image Analysis (IPRIA)
تاریخ برگزاری همایش2023-02-14 - 2023-02-16
محل برگزاری همایش1 - قم
ارائه به نام دانشگاهدانشگاه تهران - پردیس فارابی
نوع ارائهسخنرانی
سطح همایشبین المللی

چکیده مقاله

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

لینک ثابت مقاله

کلید واژه ها: traffic sign recognition؛ advanced driver assistance system؛ vision transformer؛ DeiT؛ autonomous vehicles systems