Erkenner is a Traffic Sign Detection and Recognition Mobile App.

It's a simple python script to predict the traffic signs

The goal is to find an efficient approach using a monocular camera to perform real-time traffic signs recognition and distance estimation between traffic sign and viewpoint. The next thing we want to apply, after having the distance, would be a simple feedback system for the driver as a guideline. One thing to consider is that we do not want to …

Traffic Sign Detection CNN app

Udacity Project : Design and Implementation of a CNN Pipeline for a Traffic Sign Recognition (Tensorflow Framework)

implementation of Traffic Sign Recognition on a driving dataset using Python3

Python Projects Complete code with instructions

This project is a multi-class, single-image classification to recognize traffic signs images using Convolutional Neural Networks (CNN).

Traffic Sign Recognition Project for my Internship on Prime Layer

Constructing a Traffic Sign Recognition model using deep learning and computer vision.

Deep Learning project that uses yolov5 to detect and classify traffic signals in videos.

Multi-class, single-image classification using MobileNet-CNN

This Python-based project features an intuitive graphical user interface (GUI) facilitating image uploads for the identification of essential road signs prevalent on streets, including 20kmph, 30kmph, 50kmph, stop, and right turn signs.

This code implements a CNN using TensorFlow for German traffic sign classification with the GTSRB dataset. It preprocesses data, builds the model, trains it, evaluates accuracy, and generates a confusion matrix for performance analysis.

Traffic Sign Classification with Convolutional Neural Networks in Python

Python & ML 02 - Khóa học do HCMUT EE Machine Learning & IoT Lab tổ chức giảng dạy

Transfer Learning Approach for Recognition of Iranian Traffic Signs in Self-Driving Cars

PBL project for SE

Using lenet for Traffic Sign Recognition

A deep learning model to classify Traffic Signals.