/Traffic-Sign-Classification

This project focuses on training a Deep Convolutional Neural Network (CNN) for the task of traffic sign classification. With the goal of enhancing the safety of autonomous vehicles, the CNN is designed to accurately identify and classify different types of traffic signs commonly found on roads.

Primary LanguageJupyter Notebook

Traffic-Sign-Classification

Traffic sign classification is an important task for self-driving cars. In this project, I trained Deep Convolutional Neural Network (CNN) to classify traffic sign images.

Introduction

The ability to accurately recognize and classify traffic signs is crucial for autonomous vehicles to navigate safely on roads. This project aims to develop a robust CNN model capable of identifying various traffic signs with high accuracy.

Dataset

The dataset used for this project contains images of 43 different classes of traffic signs. Each class represents a specific type of traffic sign commonly found on roads. The dataset is divided into training, validation, and test sets to facilitate model training and evaluation.