27 March 2018 Image-based corrosion recognition for ship steel structures
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Abstract
Ship structures are subjected to corrosion inevitably in service. Existed image-based methods are influenced by the noises in images because they recognize corrosion by extracting features. In this paper, a novel method of image-based corrosion recognition for ship steel structures is proposed. The method utilizes convolutional neural networks (CNN) and will not be affected by noises in images. A CNN used to recognize corrosion was designed through fine-turning an existing CNN architecture and trained by datasets built using lots of images. Combining the trained CNN classifier with a sliding window technique, the corrosion zone in an image can be recognized.
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Yucong Ma, Yang Yang, Yuan Yao, Shengyuan Li, Xuefeng Zhao, "Image-based corrosion recognition for ship steel structures", Proc. SPIE 10602, Smart Structures and NDE for Industry 4.0, 106020U (27 March 2018); doi: 10.1117/12.2296540; https://doi.org/10.1117/12.2296540
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