深層学習に基づく物体検出・認識技術を用いた二段階構造表面ひび割れスクリーニング

抄録

Recently, assessing the integrity of the structures accurately and reliably has become extremely important in various fields in order to increase operational lifetime and improve safety. Detecting surface damage such as cracks in evaluating the soundness of the structure is particularly important as it is one of the major factors causing deterioration and destruction of the structure. In this study, we develop a two-step screening system for structural surface crack by using object detection and recognition techniques based on deep learning. The accuracy of object detection depends largely on the quality and quantity of images given as training data in advance. In this study, we also construct the system to make up for the lack of training data by converting the detection results into teacher data.