Traffic Sign Recognition Using Detector-Based Deep Learning Method

Abstract

Traffic is a key element in the transportation system. Traffic is an integral part of urban life and a key element in the transportation system. Traffic safety is a major concern to prevent accidents and ensure safe mobility. Traffic accidents are one of the most common occurrences. . But on the other hand, the increase in road accidents is increasing, which can be caused by people's lack of knowledge about traffic. The main solution to overcome this problem is to increase knowledge about traffic. The application of artificial intelligence, especially object detection methods with the use of detector-based deep learning methods, is one method that has proven efficient in detecting objects in real-time.

In this research, object recognition is performed using SSD (Single Shot MultiBox Detector) where the model is trained and tested for its performance in detecting traffic signs in Indonesia. From the research results, the mAP 50 and mAP 50-95 values are 89.66% and 65.49%, respectively.

 Keyword: Deep Learning, SSD, Traffic Signs.