许明,张弓,王广涛,骆庚,郑睿博

• 1:中煤(西安)地下空间科技发展有限公司地下空间研究院

摘要(Abstract)：

探地雷达技术广泛应用于城市道路病害探测领域。道路异常检测通常需要人工目视解译来实现，存在较强的主观性和不确定性。本文基于YOLOv5目标检测算法进行设计改进，提出了一种探地雷达图像道路空洞异常检测的方法。该方法添加了一个微小目标特征检测的预测头，并引入卷积块注意力模块和高效的交并比损失函数。模型不仅迭代收敛快、回归精度高，还优化了边界框回归任务的样本不均衡问题。通过消融实验表明，改进后的方法在道路空洞检测应用中检测精度明显得到提升，平均精度均值由81.62%提升到83.90%,对道路空洞病害异常的检测效果有很大提升。

关键词(KeyWords)： 探地雷达;目标检测;注意力机制

Abstract:

Keywords:

基金项目(Foundation): 中国煤炭地质总局项目(ZMKJ-2022-JBGS03)

作者(Author): 许明,张弓,王广涛,骆庚,郑睿博

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