Aaron-Chang-AC/AIdea-Defect-Classifications-of-AOI
A Multi-input Fine-tuned Model for Automated Optical Inspection.
This project helps quality control engineers and manufacturing line supervisors automatically classify defects on circuit boards or other manufactured items. It takes images from an Automated Optical Inspection (AOI) system and outputs predictions for six types of defects, including normal, void, and various edge or particle defects. This allows for faster and more consistent defect identification.
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Use this if you need to rapidly and accurately classify defects from AOI images to improve manufacturing quality control and reduce manual inspection time.
Not ideal if your inspection process does not involve images from an AOI system or if you require a simple pass/fail judgment without detailed defect classification.
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Nov 21, 2022
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