数字海洋与水下攻防2026，Vol.9Issue(1)：32-40,9.DOI:10.19838/j.issn.2096-5753.2026.01.002
基于深度学习的水下声光图像目标检测综述
Review of Underwater Acoustic-Optical Image Object Detection Based on Deep Learning
摘要
Abstract
Underwater acoustic-optical image object detection serves as a core supporting technology for underwater intelligent operations and unmanned system collaboration,boasting irreplaceable application value in marine engineering,military reconnaissance,and other fields.The rapid iteration of deep learning technologies has provided new pathways for breaking through the technical bottlenecks of underwater object detection,yet the complex underwater detection environment has led to the lagging development of this field compared with terrestrial and aerial scenarios.To systematically sort out the technical context and clarify the development direction,a comprehensive review of the research progress on deep learning-based underwater acoustic-optical image object detection is conducted in this paper.Firstly,the evolution of object detection algorithms is summarized,the technical frameworks,advantages and disadvantages of traditional handcrafted feature methods,convolutional neural network based methods,and Transformer-based methods are comparatively analyzed.Secondly,combined with the modal characteristics of underwater detection,the application status and adaptation strategies of deep learning algorithms in underwater optical image,sonar image,and acoustic-optical joint image object detection are explained respectively.Finally,the core bottlenecks faced by the current technology are analyzed and the future research directions are prospected from the dimensions of dataset construction,model optimization,and cross-modal fusion.The collation and summary in this paper can provide theoretical reference and practical guidance for the breakthrough and implementation of underwater object detection technology.关键词
水下目标检测/深度学习/卷积神经网络/TransformerKey words
underwater target detection/deep learning/convolutional neural network/Transformer分类
信息技术与安全科学引用本文复制引用
陈俞志,王嘉,赵兵,潘汉,邱周静子..基于深度学习的水下声光图像目标检测综述[J].数字海洋与水下攻防,2026,9(1):32-40,9.基金项目
国家自然科学基金"空间连续型机器人跟踪非合作目标过程视觉伺服方法研究"(62203480) （62203480）
水下智能系统技术湖北省重点实验室开放基金项目"基于多智能体的水下目标集群探测成像与识别系统技术"(ZHJ250262) （ZHJ250262）
空天飞行器技术航空科技重点实验室基金项目"面向在轨服务和应用的自主智能操控技术研究"(J2025-STAV-03-001). （J2025-STAV-03-001）
