海南大学学报（自然科学版中英文）2026，Vol.44Issue(2)：174-184,11.DOI:10.65658/j.hndk.2025090202
基于小波变换和注意力机制的水下目标检测模型
Underwater target detection based on wavelet transform and attention mechanism
摘要
Abstract
To address the limitation of target detection performance in sidescan sonar images caused by noise interference from underwater reverberation,this paper proposes an underwater target detection model that integrates wavelet transform and an attention mechanism.The model employs wavelet transform to decompose high-and low-frequency features,and the attention mechanism adaptively enhances low-frequency global structures and high-frequency local details,effectively suppressing noise interference and highlighting target feature representations.Experimental results demonstrate that the proposed model achieves mAP@0.5 and mAP@0.5:0.95 scores of 87.0%and 56.9%,respectively,with only 2.37×106 parameters and 5.99 G FLOPs,achieving a favorable balance between high accuracy and lightweight design.The proposed model provides reliable technical support for tasks such as deep-sea mineral exploration and underwater archaeology.关键词
目标检测/侧扫声呐/沉船检测/小波变换/注意力机制Key words
object detection/side-scan sonar/shipwreck detection/wavelet transform/attention mechanism分类
信息技术与安全科学引用本文复制引用
杨明忠,刘立昕..基于小波变换和注意力机制的水下目标检测模型[J].海南大学学报（自然科学版中英文）,2026,44(2):174-184,11.基金项目
本文得到广东省海洋经济发展(海洋六大产业)专项(GDNRC[2024]44)支持. This article was supported by the Program of Marine Economy Development Special Fund(Six Marine Industries)under Department of Natural Resources of Guangdong Province(Project No.GDNRC[2024]44). （海洋六大产业）
