Field Computer Vision Project
Updated 2 years ago
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downloadsHere are a few use cases for this project:
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Sports Analysis: This model can identify different sports fields and monitor player positions, helping provide analytics for gameplay strategy refinement and individual player performance.
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Agriculture Management: In agriculture, the model can be utilized to recognize various field types (corn, soybeans, rice etc.) and the associated crop health, assisting in precision farming.
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Urban Planning: Urban planners and architects can use this tool to accurately identify different land uses such as fields in urban or rural environments, providing data for smart city development or conservation efforts.
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Automated Recreation Guide: The model can be deployed in mobile apps for trekkers, hikers, and outdoor enthusiasts to identify suitable fields for outdoor activities like camping, kite flying, or sports.
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Environmental Research: Scientists and researchers can leverage the AI model to identify different field types across global landscapes to study environmental impacts of certain practices on different field classes.
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
field-xcovi_dataset,
title = { Field Dataset },
type = { Open Source Dataset },
author = { Mohamed Badreldin },
howpublished = { \url{ https://universe.roboflow.com/mohamed-badreldin-hh84s/field-xcovi } },
url = { https://universe.roboflow.com/mohamed-badreldin-hh84s/field-xcovi },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2022 },
month = { dec },
note = { visited on 2024-12-22 },
}