海南热带海洋学院学报2026，Vol.33Issue(2)：97-105,9.DOI:10.13307/j.issn.2096-3122.2026.02.09
UCM-YOLOv11n+:面向声呐小目标检测的改进网络
UCM-YOLOv11n+:Improved Network for Sonar Small Target Detection
摘要
Abstract
Aiming to enhance the precision and robustness of fish target detection in sonar images,the UCM-YO-LOv11n+model was proposed to address the issues of noise and target blurring in challenging low-light,low-visibility un-derwater environments.The proposed model incorporates three key enhancements:1)a Unified Feature Enhancement Block(UFE)to preserve more robust features and detailed textures;2)a Multi-Head Channel Attention Block(MHCA_Block)to enable dynamic focus on critical regions in feature maps;and 3)a Content-Aware Reassembly of Fea-tures(CARAFE)module to enhance feature richness and discriminative power.Experimental results on a self-built fish sonar image dataset showed that the UFE module improved the precision from 72.9%to 77.4%,the MHCa_Block in-creased it by 4.8%,and the CARAFE module raised the mAP50 by 5.6%.Consequently,the integrated UCM-YO-LOv11n+model achieved a final mAP50 of 83.3%and a precision of 88.5%,outperforming all compared models in terms of mAP,precision,and F1-score.关键词
YOLOv11n/声呐图像/水下目标检测/小目标检测Key words
YOLOv11n/sonar image/underwater target detection/small object detection分类
信息技术与安全科学引用本文复制引用
曾佳雯,谢鑫刚,陈聪,张政睿,马玉春..UCM-YOLOv11n+:面向声呐小目标检测的改进网络[J].海南热带海洋学院学报,2026,33(2):97-105,9.基金项目
海南热带海洋学院崖州湾创新研究院重大科技计划项目(2023CXYZD001) （2023CXYZD001）
