![]() In recent years, the structural integrity of social infrastructures, which have become unsafe due to aging, has become a great concern, and how to efficiently and accurately assess their structural integrity is important in developing maintenance plans. To illustrate the applicability of the method developed here, some experiments are conducted by using the photos of running surface of concrete bridges of a monorail took by vehicle-mounted camera. For image processing, it is necessary to utilize such pre-processing techniques as binarization of pictures and morphology treatment. To save the time and load, deep learning, which is a method of artificial intelligence is introduced. ![]() ![]() While using the photos obtained by vehicle-mounted camera, the damage states of bridges can be evaluated manually, it still requires a lot of time and load. In order to reduce the inspection work, an attempt is made in this paper to develop a new inspection method using deep learning and image processing technologies. However, it requires a lot of load and expense. Usually, the inspection has been performed through the visual evaluation of experienced engineers. In Japan, all bridges should be inspected every 5 years. 2Department of Civil Engineering, Osaka Metropolitan University, Osaka, Japan.1Department of Civil and Environmental Engineering, Ritsumeikan University, Kusatsu, Japan.Yasutoshi Nomura 1*, Masaya Inoue 1 and Hitoshi Furuta 2
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