This project is made for Self Driving Car Nanodegree.

Implement Traffic Sign Detection

A traffic sign classifier with a GUI

Using Deep Learning and Convolutional Neural network to train a model to classify German Traffic Signs

Recognize the traffic sign which you cant found the name at Google.

This is my first personal project about training a deep learning algorithm for road traffic signs recognition.

Apply built-in state-of-the-art classifiers with the Keras library to Traffic Sign datasets

A deep learning model to classify Traffic Signals.

Traffic Sign Classification with Convolutional Neural Networks in Python

Traffic Sign Classification using Deep Learning.

Image Processing based Half Circle Shape Detector (traffic signs included)

This work is the final project of the DataBootcamp at IronHack in Madrid, Spain. Basically, this project consists in image recognition of traffic signs using Convolutional Neural Networks (CNN) as a exploratory study over deep learning applycations. Readers should have in mind the topic has been choosen by the author, and the project needed to b…

Final Year Project: Traffic sign detection and recognition using YOLO, and Raspberry Pi.

Traffic Sign Recognition by Convolutional Neural Network (TensorFlow)

This project is an aspect of a big project that is called the Self-Driving Car. One of the essential techniques in Self-Driving Car engineering is detecting the Traffic Sign. In this project I have used Deep Learning for recognizing the Traffic Signs.

There are several different types of traffic signs like speed limits, no entry, traffic signals, turn left or right, children crossing, no passing of heavy vehicles, etc. Traffic signs classification is the process of identifying which class a traffic sign belongs to

A repository for the paper "Real-Time Traffic Sign Recognition Based on Efficient CNNs in the Wild"