Señales de transito Computer Vision Project
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Here are a few use cases for this project:
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Smart Traffic Management Systems: This model could be used to intelligently control traffic flow in real-time, adjusting signal timings based on traffic volume, pedestrian movements, and more.
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Augmented Reality Navigation Apps: The model can enhance AR navigation applications by recognizing various signage and providing real-time updates or instructions to users, such as indicating when it's safe for pedestrians to cross or when a bus stop is nearby.
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Autonomous Vehicles: Self-driving cars, buses, and transport vehicles could use this model to understand traffic rules and signals, making decisions on when to stop, slow down, or proceed with caution.
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Assistive Technology for the Visually Impaired: The model could be integrated into aid systems (e.g. smart glasses) to help visually impaired individuals navigate urban environments by alerting them via audio cues about red/green lights, pedestrian crossings, and bus stops.
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Urban Planning and Infrastructure Development: The model could be used to identify and map the locations of traffic signs and signals across a city, aiding in effective planning and improvement of road safety and infrastructure.
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
senales-de-transito_dataset,
title = { Señales de transito Dataset },
type = { Open Source Dataset },
author = { Tesis },
howpublished = { \url{ https://universe.roboflow.com/tesis-lhuim/senales-de-transito } },
url = { https://universe.roboflow.com/tesis-lhuim/senales-de-transito },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2022 },
month = { nov },
note = { visited on 2024-12-24 },
}