Surface-Defect-Detection-in-Hot-Rolled-Steel-Strips
PublicThis 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-intelligenceclassificationcnnconvolutional-neural-networkdeep-learningdefect-detectiondetectionmanufacturingmechanical-engineeringneural-networks
Creat：2020-09-07T03:57:32
Update：2025-03-15T15:31:41
52
Stars
0
Stars Increase