MONGERY Computer Vision Project
Updated 3 years ago
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downloadsHere are a few use cases for this project:
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Quality Control in Manufacturing: Utilize the MONGERY model in manufacturing settings to identify HATALI class defects and other production errors, ensuring consistent product quality across the line.
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Food Safety Inspection: Applying the model in the food industry for inspecting food items. It can identify potential HATALI class harmful substances or inconsistencies to ensure food safety.
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Health Diagnostic Assistance: Use MONGERY in the medical field to identify HATALI on medical images such as X-rays, MRIs, or CT scans which can aid doctors with diagnosis and treatment plans for patients.
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Precision Agriculture: Farmers could deploy MONGERY in drones or other IOT devices to identify HATALI class diseases or pests in crops, enabling preventive measures before a large-scale outbreak occurs.
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Environmental Monitoring: Use this model in environmental and wildlife conservation efforts to detect any HATALI category anomalies or changes in natural settings which indicates potential threats to the ecosystem.
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
mongery_dataset,
title = { MONGERY Dataset },
type = { Open Source Dataset },
author = { kübra },
howpublished = { \url{ https://universe.roboflow.com/kubra-bihwb/mongery } },
url = { https://universe.roboflow.com/kubra-bihwb/mongery },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2022 },
month = { feb },
note = { visited on 2024-11-25 },
}