Real Time Traffic Sign Recognition Model Using Convolutional Neural Network
Manivel Kandasamy, Raju Shanmugam, Pillai Harikrishna, Kabariya Aalay P, Ania Francis, Kartik Arora · 2023
This paper aims to summarise the development of a robust and accurate system for detecting traffic signs in real-time using convolutional neural networks (CNN) and the Python programming language. By enabling autonomous vehicles to reliably identify and interpret traffic signs, the goal is to increase road safety. The proposed method seeks to handle difficulties brought on by real-world settings, such as fluctuating lighting, weather, and obstructions, by developing an efficient pre-processing method and using a CNN-based model for feature extraction and classification. The goal is to achieve high accuracy in traffic sign detection while maintaining real-time performance, making it a feasible solution for autonomous driving systems.