This repository contains a project for a class at MEF University. The goal of the project is to develop a machine learning model for recognizing German traffic signs using TensorFlow, an end-to-end open source platform for machine learning.

The dataset used in this project is the "GTSRB - German Traffic Sign Recognition Benchmark" dataset, obtained from Kaggle (https://www.kaggle.com/datasets/meowmeowmeowmeowmeow/gtsrb-german-traffic-sign). This dataset has more than 50,000 images of 43 different traffic signs.

Detailed information about the dataset can be found here

The main requirements for this project are:

• Python 3.6 or higher
• TensorFlow 2.0 or higher
• Other dependencies (numpy, pandas, etc.)

This project makes use of the "GTSRB - German Traffic Sign Recognition Benchmark" dataset available on Kaggle. The dataset can be found here.

The implementation is based on the following paper: Multi-column Deep Neural Networks for Image Classification.

This project is licensed under the MIT License - see the LICENSE file for details.