机械与电子2026，Vol.44Issue(3)：47-54,8.
基于时频双域协同与语义增强的复杂水域漂浮物检测方法
A Dual-domain Synergistic and Semantically Enhanced Method for Floating Object Detection in Complex Water Environments
摘要
Abstract
To address the issues of significant scale variations,strong background interference,and high miss detection rates of small objects in floating debris detection under complex water environments,this paper proposes a Spatial-Frequency Enhancement Network(SFE-Net).First,a Spatial-Frequency A-daptive Convolution is proposed.By employing a spatial-frequency split strategy and an adaptive fusion scheme,it overcomes the limitation of the fixed receptive fields in traditional convolution,achieving the col-laborative extraction of spatial contextual and frequency texture features,thereby significantly enhancing the perception capability for multi-scale objects.Second,a Wavelet Frequency Decoupling Module is de-signed,which decouples features into high-frequency details and low-frequency contours using Haar wavelet transform,and employs dual-path attention mechanisms to separately enhance edge textures and global semantic representations,effectively suppressing complex background noise such as water ripples and reflections.Finally,an Inner-IoU bounding box regression loss function is introduced.By incorpora-ting auxiliary bounding boxes and controlling scaling factors,it optimizes the internal similarity measure-ment of samples in feature space,addressing the problem of insufficient IoU sensitivity in small object lo-calization,and improving the convergence speed and localization accuracy of bounding box regression.Ex-perimental results on the FloW+dataset demonstrate that the proposed method achieves a mean Average Precision of 91.4%,representing an improvement of 8.7 percentage points over the original YOLOv8n.Meanwhile,the model parameters are reduced by 36.7%,and the inference speed reaches 214 frames per second,significantly enhancing detection performance while ensuring real-time capability.关键词
目标检测/空频自适应/小波变换/Inner-IoU/水面漂浮物Key words
object detection/spatial-frequency adaptive/wavelet transform/Inner-IoU/water surface floating objects分类
信息技术与安全科学引用本文复制引用
张思思,滑文强..基于时频双域协同与语义增强的复杂水域漂浮物检测方法[J].机械与电子,2026,44(3):47-54,8.基金项目
西安航空职业技术学院2023年度校级科研计划项目(23XHZK-15) （23XHZK-15）
