Broiler Instance Segmentation Computer Vision Project
Updated a year ago
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Here are a few use cases for this project:
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Poultry Health Management: This model could be used to track individual broilers' movement, behavior, or eating patterns, which would help identify early signs of disease or stress among the flock.
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Livestock Monitoring: Farmers can use it to monitor and manage broiler numbers in the poultry farm, ensuring a constant count and detecting any unusual decrease that could signify theft or loss.
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Broiler Research: For scientists and researchers studying broiler behavior or genetics, the model can help to identify and track individual broilers for detailed observation and data collection.
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Animal Welfare: Animal welfare organizations could use the model to ensure safe and non-crowded living conditions for broilers, as it offers an automated way to count and track the birds, helping enforce rules on the maximum number of chickens per cage.
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Broiler Trading & Supply Monitoring: Companies in the poultry supply chain can use this model to verify the quality and quantity of broilers in supply and demand, reducing broiler trading discrepancies and fraud.
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
broiler-instance-segmentation_dataset,
title = { Broiler Instance Segmentation Dataset },
type = { Open Source Dataset },
author = { rawitchK },
howpublished = { \url{ https://universe.roboflow.com/rawitchk/broiler-instance-segmentation } },
url = { https://universe.roboflow.com/rawitchk/broiler-instance-segmentation },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { aug },
note = { visited on 2024-11-13 },
}