GENERATION OF SURFACE PREPARATION IMAGES FOR WEATHERING STEEL BRIDGES USING GENERATIVE ADVERSARIAL NETWORKS

Abstract

The surface preparation grade of steel bridges is generally judged by visual inspection. There is a high possibility that a difference in evaluation by the engineer. The authors are trying to develop the support system for classify the surface preparation grade using deep learning. In order to improve the generalization performance of the system, it is necessary to enhance the teacher images used for training. In the present paper, it was confirmed that the generalization performance of the support system for classify the surface preparation grade can be improved by enhancing the teacher images with images generated by GAN. The SSIM value confirmed that mode collapse can be identified from the similarity between the teacher image and the generated image by GAN.