traffic-sign-detection and Traffic-Sign-classifier-with-Deep-Learning

Detection and classification are complementary stages in a traffic sign understanding pipeline—the first tool identifies where signs are located in images, while the second classifies what type of sign each detected region contains.

Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 24/25
Maintenance 0/25
Adoption 3/25
Maturity 16/25
Community 14/25
Stars: 336
Forks: 101
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stars: 4
Forks: 3
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: Apache-2.0
Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About traffic-sign-detection

aarcosg/traffic-sign-detection

Traffic Sign Detection. Code for the paper entitled "Evaluation of deep neural networks for traffic sign detection systems".

This project provides pre-trained models and code for automatically identifying traffic signs in images or video. It takes raw image data as input and outputs the location and type of traffic signs present. This is designed for researchers and engineers developing advanced driver-assistance systems (ADAS) or autonomous vehicle technology.

autonomous-driving traffic-management computer-vision ADAS object-detection

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

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

Classify traffic signs with Artificial neural networks

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