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Chintya, Ni Putu Praja,전기성,백승일,김원국 한국측량학회 2022 한국측량학회지 Vol.40 No.6
Ports are one of the important social infrastructures that function as central transportation hubs for goods. Although fast and continuous monitoring is essential for efficient infrastructure management, it has been timeand labor consuming with human’s direct inspection. Effective monitoring, including real-time monitoring, hasdrawn significant attention since the advent of UAVs (Unmanned Aerial Vehicles), robotics, IoT (Internet ofThings), and AI (Artificial Intelligence) technologies. In this study, we develop a deep learning-based changedetection model for multitemporal images acquired from UAV’s for breakwater facility. SNUNet-CD algorithm,a combination of Siamese Network and NestedUnet, was used for detecting changes in dissipating blocks in thefacility, and four data collection schemes were tested for the study site of Yongho Port, located in Busan, SouthKorea. The results showed that accuracy performance is around 0.8 in precision, recall, and F1-score, when themodel was trained with site-specific image data sets fortified by data augmentation.