The data augmentation for UAV river patrol AI using generated image by generative models such as Stable Diffusion

Abstract

The data in the civil engineering field is less data with much variety. Drone river patrols fly vast river areas and detect illegal dumping, including general garbage, using AI. The patrol drones are not constantly flying, they are rarely captured by aerial images, and it is even more difficult to detect temporary illegal occupation. In previous studies, it has been confirmed that adding images taken on the ground with different angles of view to the learning data improves learning, but the number of images is required for training even if the images are taken on the ground. In order to improve the learning of the detection model, this study verified whether the image for data augmentation can be generated and learned by image generation AI such as Stable Diffusion.