Implementation of Single Shot MultiBox Detector in TensorFlow, to detect and classify traffic signs

Traffic signs detection and classification in real time

[DEPRECATED] Traffic sign detector and classifier that uses dlib and its implementation of the Felzenszwalb's version of the Histogram of Oriented Gradients (HoG) detector

Deep leaning for traffic sign classification in keras and python

Türkiye Trafik İşaretleri Veriseti - Turkish Traffic Sign Dataset

Autonomous Driving Simulator for the Portuguese Robotics Open

Traffic sign classification for the German Traffic Sign Dataset

German Traffic Sign Recognition Benchmark (GTSRB) AlexNet pycaffe model. http://benchmark.ini.rub.de/

Training a Faster R-CNN from scratch on LISA Traffic Signs dataset using TensorFlow Object Detection API

Synthetic traffic sign detectron

In this project, deep neural networks and convolutional neural networks are used to classify traffic signs. A model is trained so it can decode traffic signs from natural images by using the German Traffic Sign Dataset. After the model is trained, the model is tested on new images of traffic signs that are found on the web

Tie - Font Conversion of The Finnish Traffic Sign Typeface

The German Traffic Sign Benchmark is a multi-class, single-image classification challenge. Humans are capable of recognizing the large variety of existing road signs with close to 100% correctness.Then what about machines, Can we make them intelligent like humans ?

Detection and recognition of traffic signs.

Udacity Self Driving Car Nanodegree - Traffic Sign Classifier

This project recognises the traffic sign based on training data.

A python-based software application that uses AlexeyAB's YOLO detection algorithm to detect regulatory and warning traffic signs with voice assistance.

Traffic Signs classification project using GTSRB dataset using a modified VGGNet architecture in tensorflow