This is a Classifier Algorithm that can classify German Traffic-Signs. It uses the good old convolution network inspired by the Nvidia Model used in their self-driving car.

This Project is on classifying traffic signs... I have used a Deep Convolution Neural Network which classifies traffic sign images

A short evaluation of CNN architectures/papers for German Traffic Sign Recognition Benchmark (GTSRB)

I utilized deep neural networks and convolutional neural networks to classify traffic signs. I trained and validated a model so it can classify traffic sign images using the German Traffic Sign Dataset.

Classify traffic signs from the German Traffic Sign Dataset

Self-Driving Nano Degree Program : Traffic Sign Recognition

基于 ResNet 的国内交通信号图标分类

Built and trained a deep neural network to classify traffic signs, using TensorFlow. Experimented with different network architectures. Performed image pre-processing and validation to guard against overfitting. The datasets are collected from the German Traffic Sign for training and random traffic signs downloaded from internet for testing.

Traffic Sign Classification using Deep Learning, done as a part of Udacity Self Driving Car Nanodegree Program

Traffic sign recognition project of Udacity Self-driving car nano degree

deep-learning

Udacity Self Driving Car Nanodegree - Traffic Sign Classification

Udacity's Self Driving Car Nanodegree program Project 2: Traffic Sign Classifier

Classify road signs using a deep convolutional neural network.

Classify Traffic Signs.

This is a Deep Learning Project to classify German Road Signs using deep neural networks and image processing.

Project 2 of Udacity Self Driving Car Nanodegree