wx_3 Computer Vision Project
Updated 2 years ago
Here are a few use cases for this project:
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Quality Control in Manufacturing: The "wx_3" model could be useful in automating the quality inspection process in manufacturing industries. It can alert personnel when the detected metal class or defects (scratch, heiyin, keceng) do not meet the acceptance criteria.
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Scrap Metal Sorting: The identification of different metal classes can aid in automated sorting of scrap metal, improving speed and accuracy and reducing manual work in recycling facilities.
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Artifact Examination: Museums or archeological institutions might use the model to analyze metallic artifacts. It could help detect signs of wear and tear such as scratches or other imperfections and aid in categorizing the items based on the metal class.
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Automotive Industry: Within the car manufacturing and maintenance sector, the "wx_3" model could be used to detect and classify damage in the metal parts of the vehicles.
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Machinery Maintenance: In industries where heavy machinery is used, the model could be used to predict machinery failure by detecting and classifying signs of deterioration on the machinery's metal components.
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
wx_3_dataset,
title = { wx_3 Dataset },
type = { Open Source Dataset },
author = { wx_dl },
howpublished = { \url{ https://universe.roboflow.com/wx_dl/wx_3 } },
url = { https://universe.roboflow.com/wx_dl/wx_3 },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2022 },
month = { jul },
note = { visited on 2024-11-24 },
}