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

Traffic signs detection and classification in real time

Türkiye Trafik İşaretleri Veriseti - Turkish 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

Detection and recognition of traffic signs.

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

This Python script generates a synthetic dataset of traffic sign images in COCO format, intended for training and testing object detection models. The dataset includes various traffic sign overlays placed on diverse background images, offering a wide range of scenarios to enhance model robustness.

Safe Sightings of Signs and Signals (SSOSS): Software to verify visible traffic signs & signals using GPS, video files.

Autonomous driving in urban environments

Assets and files for an app for quickly adding german traffic signs to OpenStreetMap

Bachelor's Thesis - Real-time traffic-signs recognition using YOLOv3

Project description, sample dataset and scripts for "Mobile mapping solutions for the update and management of traffic signs in a road cadastre free and open-source GIS architecture" for FOSS4G 2023.

Using deep learning to classify different traffic signs

Detect and recognise traffic lights using Hough circle transform implemented with OpenCV and Python

The Road Sign Recognition project is a real-time detection system designed to recognize road signs across 43 different classes. The project leverages the YOLOv5 model, which is trained on the GTSRB - German Traffic Sign Recognition Benchmark dataset.

Classified traffic signs using Convolutional Neural Networks

Detect and classify traffic signs with Faster R-CNN and ResNet neural networks from photos as a team project for Convolution Neural Networks (KNN) Course at BUT FIT.