In Japan, the age-related deterioration of many public roads, which were constructed in the 1960s, is demandingmaintenance solutions. We propose a convolutional neural network (CNN)-based method to convert the originalimage to a pseudo normal road surface image. The converter selectively replaces only the abnormal data of animage with pixels corresponding to normal features, thereby creating an output image without abnormal parts.We aim to detect anomalies on the road surface by calculating the difference between a raw input image and thegenerated PNI image. Our experimental results confirm the effectiveness and usefulness of our method.
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