Structural defect segmentation using a semi-supervised algorithm integrating YOLO and the segment anything model

Gauthami Vijayakumar Kuttuva

doi:10.1016/j.autcon.2025.106709

2025-12-11

PRE

Gauthami Vijayakumar Kuttuva

J. Prawin *

DOI：10.1016/j.autcon.2025.106709

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摘要

En 中文

• 两阶段半监督YOLOv11–SAM框架实现了对土木缺陷的精细实例分割。 • 区域级标注将标注工作量最多减少30倍，同时保持高分割精度。 • 所提出的模型具有良好的跨数据集泛化能力，在多变纹理和光照条件下优于监督方法。 • 定向边界框能准确捕捉不规则裂缝，提高量化精度并减少数据增强需求。

期刊

Automation in Construction

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11.5

论文数:

6.3K

被引数:

4.2W

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