Recently, there have been many studies to classify the image-based damage of bridge using the deep learning and to evaluate the condition. These attempts are one of the ways to overcome limitations of visual inspection through inspectors, and it is also aimed to reduce the cost of necessary maintenance budget by enabling accurate and rapid damage assessment of rapidly growing old facilities and difficult parts of visual inspection. However, it is possible to classify and quantitatively express simple damage (one damage classification such as cracks) with image information (big data) of bridges, but classification and quantification of complex damage can be done by using one deep learning is a limit. Therefore, this study presents considerations and a method to be used for damage detection on the image basis using deep learning.

Abstract
 1. 서 론
 2. 영상기반 딥러닝을 이용한 교량 손상 탐지를 위한 고려사항
 3. 영상기반 딥러닝을 이용한 손상 탐지 방법
 4. 결 론
 참고문헌

• 정현준(한국시설안전공단 시설성능연구소) | Jung Hyun Jun
• 남우석(한국시설안전공단 시설성능연구소) | Nam Woo Suk 교신저자
• 클레멘타인(㈜핀텔) | Nyirarugira Clementine
• 김규선(한국시설안전공단 시설성능연구소) | Kim Gyu Seon
• 김동기(㈜핀텔) | Kim Dong Key