canned-food-surface-defect Computer Vision Project
Updated 4 months ago
Metrics
Here are a few use cases for this project:
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Quality Control in Food Packaging Industries: This model can be used to automatically inspect canned food before it reaches the consumers, identifying defects on the can surface potentially caused during the manufacturing process. Thus, it helps eliminate potential hazards and to maintain high-quality standards.
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Supply Chain Monitoring: Companies in the logistics and retail sectors can use this model to evaluate the condition of canned food received at warehouses or retail stores, ensuring only defect-free products make it to the shelves.
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Food Safety Compliance: Regulatory bodies can employ this model in routine inspections of food manufacturing facilities to ensure compliance with food safety and packaging guidelines.
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Consumer Oriented Apps: Developers can create mobile apps that let consumers use their smartphone camera to check for defects before purchasing canned food from stores or receiving home deliveries.
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Recycling Process: Recycling facilities can implement this model to identify and separate potentially dangerous cans with major and critical surface defects, contributing to a safe and more efficient recycling process.
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
canned-food-surface-defect_dataset,
title = { canned-food-surface-defect Dataset },
type = { Open Source Dataset },
author = { Canned Food Surface Defect Classification },
howpublished = { \url{ https://universe.roboflow.com/canned-food-surface-defect-classification/canned-food-surface-defect } },
url = { https://universe.roboflow.com/canned-food-surface-defect-classification/canned-food-surface-defect },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2024 },
month = { jul },
note = { visited on 2024-11-23 },
}