fault Object Detection Dataset and Pre-Trained Model by wafer

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Explore Dataset

Here are a few use cases for this project:

Quality Control in Manufacturing: This "fault" model could be used in various manufacturing processes such as in producing plastic items, textiles, or ceramics where such faults like Sagging, InTiO2 (impurities in Titanium Dioxide), fm (fault marks), MBH (major bubble hole), or bubble faults commonly occur. This would automate the process, improving efficiency, reducing costs, and minimizing human error.
Infrastructure Maintenance: This system could be applied for detecting faults in civil structures like bridges, buildings or pipelines, where the mentioned faults might indicate some damages that need immediate attention.
Paint and Coating Industry: The appearance of sagging, bubble, or others in paints and coatings can compromise the finished product's quality. By detecting these faults early, the manufacturer can improve their product's quality and durability.
Product Inspection in E-commerce: In online shopping platforms, the "fault" system can be used to inspect returned items for any signs of the listed defects to ensure accurate grading and proper sale value.
Art Restoration & Conservation: Art restorers can use the "fault" computer vision model to identify abnormalities or damages in various artworks, such as sagging or bubbles, helping to maintain and conserve these works effectively.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite this Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{ fault-qxbdk_dataset,
    title = { fault Dataset },
    type = { Open Source Dataset },
    author = { wafer },
    howpublished = { \url{ https://universe.roboflow.com/wafer-c2ull/fault-qxbdk } },
    url = { https://universe.roboflow.com/wafer-c2ull/fault-qxbdk },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2023 },
    month = { jun },
    note = { visited on 2023-12-09 },
}