합성곱 신경망을 이용한 정사사진 기반 균열 탐지 기법
Crack Detection Technology Based on Ortho-image Using Convolutional Neural Network
- 주제(키워드) Ortho-image , UAV , Machine learning , Crack detection , CNN
- 발행기관 한국공간구조학회
- 발행년도 2022
- 총서유형 Journal
- KCI ID ART002862224
- 본문언어 한국어
초록/요약
Visual inspection methods have limitations, such as reflecting the subjective opinions of workers. Moreover, additional equipment is required when inspecting the high-rise buildings because the height is limited during the inspection. Various methods have been studied to detect concrete cracks due to the disadvantage of existing visual inspection. In this study, a crack detection technology was proposed, and the technology was objectively and accurately through AI. In this study, an efficient method was proposed that automatically detects concrete cracks by using a Convolutional Neural Network(CNN) with the Orthomosaic image, modeled with the help of UAV. The concrete cracks were predicted by three different CNN models: AlexNet, ResNet50, and ResNeXt. The models were verified by accuracy, recall, and F1 Score. The ResNeXt model had the high performance among the three models. Also, this study confirmed the reliability of the model designed by applying it to the experiment.
more