CHICKEN[YOLO] Computer Vision Project
Here are a few use cases for this project:
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Poultry Health Monitoring: The model can be used in poultry farms to rapidly and accurately identify the health condition of chickens based on their manure, reducing time and costs on traditional lab tests.
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Veterinary Research: In academic or medical research, the model can be used to study different chicken diseases effectively by classifying them based on observed manure conditions.
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Livestock Disease Prediction: The model could be used to monitor and alert farmers about potential SALMO or Coccidiosis outbreaks in a flock, by identifying early signs from the manure before the disease spreads causing more damage.
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Manure Quality Control: For agriculture businesses, the model can be used to assess the quality and health condition of chicken manure before it is used as fertilizer, ensuring that crops will not be contaminated.
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Biosecurity Strategy: Government agencies can utilize the model to inspect imported live poultry or poultry products to avoid introducing and spreading diseases.
Trained Model API
This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.
Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
chicken-yolo-tpynr_dataset,
title = { CHICKEN[YOLO] Dataset },
type = { Open Source Dataset },
author = { PROJECTS },
howpublished = { \url{ https://universe.roboflow.com/projects-mmpxg/chicken-yolo-tpynr } },
url = { https://universe.roboflow.com/projects-mmpxg/chicken-yolo-tpynr },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { may },
note = { visited on 2024-05-05 },
}
Connect Your Model With Program Logic
Find utilities and guides to help you start using the CHICKEN[YOLO] project in your project.
