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Sheet_material_defect_dataset

A high-quality dataset of sheet surface defects released by Linyi Vocational College of Science and Technology, covering 283G images with 10 typical defect types for model training and validation.

AccessFree to access
LicenceLicense statement is still being checked
Producer临沂科技职业学院

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Machine learning & corporaFree to access

Key facts

InstitutionLinyi Vocational College of Science and Technology
CoverageSheet surface defects
Time spanSee official page
Scale283G

Contents & fields

This dataset contains 283G high-quality images of sheet surface defects, covering 10 typical defect types such as scratches, pits, and dirt. Data includes images, XML files, and TXT files, with a scientific split into training and validation sets. No field-level description is disclosed on the source page.

Research uses

Suitable for research on sheet surface defect detection, industrial quality inspection, computer vision classification, and object detection.

Information comes from the source page. Please check that page for current details and terms.

Keywords

sheet defectsurface inspectionindustrial quality inspectiondeep learningimage classificationobject detection

Access and licence

Licence: License statement is still being checked | Free to access

Why this is hard to get on your own

The industrial quality inspection field lacks high-quality, well-annotated sheet defect datasets; this dataset provides 283G images and 10 defect types for direct model training.

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