pineapple Computer Vision Project
Updated 2 years ago
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Metrics
Here are a few use cases for this project:
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Agriculture Evaluation: The model can be used by farmers or agricultural companies to assess the health and ripeness of pineapples in the field, helping to optimize harvest time and increase yield.
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Quality Control in Food Industries: Manufacturers can employ the model to conduct quality control inspection in real-time on the production line, checking the quality, size, and maturity of pineapples to maintain consistent product standards.
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Grocery Retail Assistance: Grocery stores can implement this model to automate the process of inventory assessment, detecting overripe or damaged pinapples, and thus helping with restocking and waste reduction.
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Augmented Reality Education: The model can be integrated into an AR application used for educational purposes, helping students to learn about different parts of a pineapple or different types of pineapples through interactive visualization.
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Biometric Authentication for Greenhouses: Using this model, access to specific areas containing pineapples within a smart greenhouse could be limited to only the staff members responsible for them – the camera would scan for the presence of a pineapple as part of the biometric checking process. This would ensure that only authorized personnel are able to interact with these areas.
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
pineapple-xgyxq_dataset,
title = { pineapple Dataset },
type = { Open Source Dataset },
author = { yolov5 },
howpublished = { \url{ https://universe.roboflow.com/yolov5-dxhko/pineapple-xgyxq } },
url = { https://universe.roboflow.com/yolov5-dxhko/pineapple-xgyxq },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { jun },
note = { visited on 2024-12-25 },
}