Traffic Sign Recognition System using CNN

This paper involves developing a system for recognizing traffic signs using computer vision techniques. The objective is to improve road safety by providing real-time detection and classification of traffic signs that can be used to alert drivers and provide valuable information about the road ahead. The system uses convolutional neural network (CNN) based deep learning model to train and classify the signs based on learning from the training images. The paper also includes the development of a user-friendly interface for displaying the detected signs and their corresponding meanings to the driver. The proposed system has the potential to significantly reduce the number of accidents caused by driver error and improve the overall efficiency of transportation.