JSAI2019

Presentation information

General Session

General Session » [GS] J-13 AI application

[4C3-J-13] AI application: diagnosis

Fri. Jun 7, 2019 2:00 PM - 3:40 PM Room C (4F International conference hall)

Chair:Tomoyuki Kimoto Reviewer:Megumi Kurayama

3:20 PM - 3:40 PM

[4C3-J-13-05] Automatic detection method of dam pop-out by deep learning

〇Yuri Shimamoto1, Takato Yasuno1, Minoru Aihara1, Junichiro Fujii1, Junichi Okubo1, Masazumi Amakata1 (1. Yachiyo Engineering Co.,Ltd.)

Keywords:infrastructure, Maintenance, inspection, dam, image processing

In recent years, the aging of infrastructures including dams has become a problem, and it is urgent to develop appropriate and efficient inspection methods. In this research, we propose a method that enables deep learning to accurately and efficiently understand the positional distribution of dam pop-out. In this method, we used a semantic segmentation which is one of the object recognition methods for the image captured by the dam body with UAV, and made a pop out judgment on a pixel unit. As a result, it was possible to detect the position of the pop out almost.