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Traffic-sign recognition ( TSR) is a technology by which a vehicle is able to recognize the traffic signs put on the road e.g. "speed limit" or "children" or "turn ahead". This is part of the features collectively called ADAS. The technology is being developed by a variety of automotive suppliers.
Browse public repositories on GitHub that use deep learning, computer vision, and machine learning for traffic sign recognition. Find code, datasets, papers, and projects related to traffic sign detection, classification, and deployment.
11 de may. de 2023 · A comprehensive review of traffic sign recognition methods using machine learning and deep learning techniques. The paper covers preprocessing, feature extraction, classification, datasets, and future research prospects in this field.
Learn how to create a deep learning architecture that can identify traffic signs with close to 98% accuracy on the test set. The post covers pre-processing, model architecture, data augmentation, and visualization of activation maps.
Find the latest research papers, benchmarks, datasets and libraries for traffic sign recognition, a computer vision task of identifying traffic signs in images or videos. Compare models, methods and results for various datasets and scenarios.
4 de nov. de 2019 · Traffic sign classification is the process of automatically recognizing traffic signs along the road, including speed limit signs, yield signs, merge signs, etc. Being able to automatically recognize traffic signs enables us to build “smarter cars”.
7 de mar. de 2022 · This article evaluates the performance of YOLOv5 and SSD for traffic sign recognition (TSR) using a new dataset. It compares the accuracy, speed and robustness of the two deep learning models for TSR and provides insights for future research.
