Surface-Defect-Detection-in-Hot-Rolled-Steel-Strips

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This project aims to automatically detect surface defects in Hot-Rolled Steel Strips such as rolled-in scale, patches, crazing, pitted surface, inclusion and scratches. A CNN is trained on the NEU Metal Surface Defects Database which contains 1800 grayscale images with 300 samples of each of the six different kinds of surface defects.

artificial-intelligence classification cnn convolutional-neural-network deep-learning defect-detection detection manufacturing mechanical-engineering neural-networks

Creat：2020-09-07T03:57:32

Update：2025-03-15T15:31:41

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