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Metal component surfaces are random textured and non-smooth. There are many stains on the surface of metal component that are similar to the gray scale of the scratches. The scratches have non-uniform gray distribution, various shapes, and low contrast in their background, posing challenges in accurate scratch detection. This paper presents a method for detecting weak scratches on metal component surfaces based on deep convolutional neural networks (DCNNs). First, a DCNN is trained usingdoi:10.1109/access.2019.2894863 fatcat:eopt7wimifbpllfnd4duffavda