Segmentation Damage Tire Computer Vision Project
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Here are a few use cases for this project:
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Tire Manufacturer Quality Control: This model could be used in tire manufacturing facilities to automatically detect and classify damaged tires in the production line, ensuring only high-quality products are distributed.
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Automotive Repair and Maintenance: Car repair shops may use this model to automatically scan and determine the type of tire damage, helping them to accurately diagnose problems and suggest necessary repairs to customers.
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Road Safety Authorities: The model could be used by road safety authorities and inspection centers to ensure the roadworthiness of vehicles, as part of routine checks or insurance assessments.
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Used Car Dealerships: This computer vision model can be useful for used car dealerships to verify the condition of tires in the cars they are selling or buying, enhancing their decision-making process and ensuring the safety of customers.
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Autonomous Vehicles: Autonomous vehicles could use this model as part of their on-board systems to monitor tire health in real-time, helping the vehicle identify when it may need tire-related maintenance.
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
segmentation-damage-tire_dataset,
title = { Segmentation Damage Tire Dataset },
type = { Open Source Dataset },
author = { Print },
howpublished = { \url{ https://universe.roboflow.com/print/segmentation-damage-tire } },
url = { https://universe.roboflow.com/print/segmentation-damage-tire },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { jun },
note = { visited on 2024-12-31 },
}