Traffic-Sign-classifier-with-Deep-Learning and Traffic-Sign-Detection-Using-CNN

Maintenance 0/25
Adoption 3/25
Maturity 16/25
Community 14/25
Maintenance 0/25
Adoption 3/25
Maturity 16/25
Community 12/25
Stars: 4
Forks: 3
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: Apache-2.0
Stars: 4
Forks: 1
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About Traffic-Sign-classifier-with-Deep-Learning

neerajd12/Traffic-Sign-classifier-with-Deep-Learning

Classify traffic signs with Artificial neural networks

This helps classify images of traffic signs, identifying what type of sign is present. It takes in an image of a traffic sign and outputs its classification, such as a 'stop' sign or 'yield' sign. This is useful for engineers and researchers working on autonomous vehicles or smart city infrastructure.

autonomous-driving traffic-management computer-vision image-recognition transportation-safety

About Traffic-Sign-Detection-Using-CNN

MustafaBanatwala04/Traffic-Sign-Detection-Using-CNN

An application built with TensorFlow and Keras for traffic sign detection. Utilizes Convolutional Neural Networks (CNNs) to accurately identify and classify traffic signs from images. Achieved an accuracy of 98.89% on the test dataset. Simply upload images to classify traffic signs. Contributions welcome!

This application helps you identify and classify traffic signs accurately from images. You upload a photo containing a traffic sign, and the system tells you what sign it is. This is ideal for researchers or developers working on real-time traffic sign recognition systems, autonomous vehicles, or advanced driver-assistance systems.

autonomous-driving traffic-management image-classification driver-assistance-systems transportation-safety

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