计算机科学与探索2025，Vol.19Issue(11)：2981-2993,13.DOI:10.3778/j.issn.1673-9418.2501001
双重细化门控自适应融合的道路裂缝检测算法
Dual-Refinement Gate-ControlledAdaptive FusionAlgorithm for Road Crack Detection
摘要
Abstract
The road crack detection task presents various defect types and complex anomaly regions.The current object detection algorithms suffer from redundant feature processing in channel and spatial dimensions,blind fusion of stage information,and other issues,leading to low network efficiency and loss of crucial information.This paper introduces a dual-refinement gate-controlled adaptive fusion network(DR-DETR)that achieves dual-refinement processing of features in channel and spatial dimensions in latent space,addressing previous issues and enhancing road crack detection accuracy.This paper constructs a dual-refinement information distillation mechanism in channel and spatial dimensions,distills redundant features separately in channel and spatial dimensions,reduces redundant processing of features by the network,and achieves efficient representation of crucial features.Aiming at the coarse-grained fusion of stage features,a feature-gated fine-grained adaptive fusion module(FGAF-Fusion)is proposed,which utilizes enhanced stripe-wise dilated convo-lutions to capture global information,then employs contrastive perceptual attention for inter-channel interaction and fusion,while utilizing a gate-adaptive fusion mechanism to select critical semantic information of small targets.This paper designs the Res-DCNv3 module,utilizing the flexibility of DCNv3 deformable convolutions to accurately extract diverse features of road cracks with varying morphologies.Experimental results on the RDD2022 public dataset demonstrate that the proposed DR-DETR achieves mAP0.50 and mAP0.50:0.95 of 51.7%and 24.9%,respectively,representing improvements of 4.2 and 3.3 percentage points over RT-DETR.In road crack object detection tasks,the proposed DR-DETR can effectively detect various types of road defects,demonstrating highly competitive detection results and good robustness.关键词
缺陷检测/双重细化/门控自适应融合/RT-DETR/可变形卷积Key words
defect detection/dual refinement/gate-controlled adaptive fusion/RT-DETR/deformable convolution分类
计算机与自动化引用本文复制引用
冯永安,张紫扬,张旭..双重细化门控自适应融合的道路裂缝检测算法[J].计算机科学与探索,2025,19(11):2981-2993,13.基金项目
国家自然科学基金面上项目(51874166,52274206) （51874166,52274206）
国家自然科学基金青年基金(51904144). This work was supported by the General Program of the National Natural Science Foundation of China(51874166,52274206),and the Youth Fund of the National Natural Science Foundation of China(51904144). （51904144）
