In the field of industrial manufacturing, product defect detection is a key link to ensure quality and reduce costs, especially in industries such as textiles, electronics, and automobiles. Traditional manual detection has pain points such as low efficiency (missed detection rate up to 10% -50%), inconsistent standards, and difficult data traceability. This solution is based on AI visual inspection technology and utilizes a cloud edge architecture that integrates software and hardware to achieve precise, real-time, and automated defect identification. The plan focuses on the special characteristics of flexible materials such as fabrics, combined with deep learning and multimodal imaging technology, covering multiple industry scenarios from textile fabrics to electronic components.

Dedicated to the research and development of core visual algorithm technologies, product innovation and industry applications, empowering AI+ diversified scenarios, facilitating industrial upgrading
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