Hangcheng Dong

Abstract Accurate detection of dam cracks from Unmanned Aerial Vehicle (UAV) imagery is crucial for structural health monitoring. However, prevailing methods face significant challenges in achieving a balance between the precise identification of minuscule cracks and computational efficiency when processing high-resolution images. To overcome these limitations, this paper proposes HiResDC-YOLO, a novel deep learning framework based on an enhanced YOLOv12 architecture.

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