计算机工程与应用2025，Vol.61Issue(10)：372-380,9.DOI:10.3778/j.issn.1002-8331.2404-0256
改进YOLOv7-Tiny的道路裂缝检测算法
Improved YOLOv7-Tiny Road Crack Detection Algorithm
摘要
Abstract
In terms of road engineering,road crack detection plays an important role.Aiming at the problems of low accu-racy and efficiency in current road crack detection algorithms,a road crack detection lightweight algorithm YOLOv7-TPSF based on YOLOv7-Tiny is proposed.Partial convolution PConv is used to replace some 3×3 convolution layers with more consumption parameters in the original network to reduce the number of model parameters and improve the training speed of the model.Combining the advantages of the feature fusion network BiFusion Neck and the weighted bidirectional feature pyramid BiFPN,a new feature fusion module Bi-FusFPN is proposed to reduce network computation and strengthen the ability of multi-scale feature fusion.A non-parametric attention mechanism SimAM is added at the output end to further improve the detection ability of large,medium,and small targets.The experimental results show that compared to the YOLOv7-Tiny algorithm,the number of network parameters and computations in the YOLOv7-TPSF algorithm are reduced by 31.7%and 34.6%,the accuracy and detection speed are improved by 3.7%and 9.7%,meeting the requirements for accuracy and real-time detection of road cracks to a certain extent.关键词
道路裂缝检测/YOLOv7-Tiny/轻量型/注意力机制/特征融合模块Bi-FusFPNKey words
road crack detection/YOLOv7-Tiny/lightweight/attention mechanism/feature fusion module Bi-FusFPN分类
计算机与自动化引用本文复制引用
王启涵,刘超..改进YOLOv7-Tiny的道路裂缝检测算法[J].计算机工程与应用,2025,61(10):372-380,9.基金项目
江苏省"六大人才高峰"项目(XXRJ-012). （XXRJ-012）
