Improved YOLOv8n-based bridge crack detection algorithm under complex background conditions

Nature·Apr 16

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Researchers have developed improved algorithms for detecting cracks in various structures, including bridges, using enhanced versions of the YOLO model. These algorithms, such as YOLOv8n and YOLOv11, incorporate features like feature fusion and optimization to improve detection accuracy under complex conditions. The applications of these algorithms extend to detecting cracks in other structures, including buildings, ventilation shaft walls, and retaining walls.

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