Classification of metal screw defect detection using FOMO on edge impulse / Muhammad Imran Daing
Surface defects in metal screws are typically identified through manual inspection, which can be prone to human error. The introduction of deep learning, particularly in visual detection, offers a significant improvement in the effectiveness and precision of defect identification. This project uses...
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| Format: | Student Project |
| Language: | en |
| Published: |
2025
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| Online Access: | https://ir.uitm.edu.my/id/eprint/117981/1/117981.pdf https://ir.uitm.edu.my/id/eprint/117981/ |
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