yolo Computer Vision Project
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Here are a few use cases for this project:
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Precision Manufacturing: The YOLO model can be used in manufacturing settings to identify defects in precision-made parts such as engine components, circuit boards, or semiconductor wafers.
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Quality Control in Food Industry: The model could be useful in identifying defective food items on a production line, for example, spoiled fruits in a packing house or irregularly shaped bakery products.
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Pharmaceutical Packaging Quality Check: The computer vision system could be used to inspect pharmaceutical packages, detecting defects like broken seals, damaged packaging, or incorrect labeling.
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Surface Defect Detection in Metal Industry: This model could be applied to identifying surface defects (cracks, pits, scratches) in metal plates or tubes during the production process.
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Tyre Manufacturing: It can be used to find defects or irregular patterns in the manufacture of tires, enhancing quality control by detecting problems early in the 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{
yolo-jteva_dataset,
title = { yolo Dataset },
type = { Open Source Dataset },
author = { student 02 },
howpublished = { \url{ https://universe.roboflow.com/student-02/yolo-jteva } },
url = { https://universe.roboflow.com/student-02/yolo-jteva },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2022 },
month = { apr },
note = { visited on 2024-11-21 },
}