数字海洋与水下攻防2024，Vol.7Issue(1)：47-53,7.DOI:10.19838/j.issn.2096-5753.2024.07.006
基于YOLO算法的海洋中尺度涡三维结构构建
3D Strucure Construction of Mesoscale Eddies Based on YOLO Intelligent Algorithm
摘要
Abstract
Mesoscale eddies are a common marine mesoscale phenomenon.Studying the distribution and motion characteristics of mesoscale eddies plays an important role in shipping,climate,and military affairs.At present,the identification of marine mesoscale eddies is a hot research topic in the field of oceanography and computer science.In this paper,the two-dimensional identification and three-dimensional structure construction of mesoscale eddies are studied and analyzed by using deep learning method and framework.Firstly,the global marine physics reanalysis data are obtained to visualize streamlines to build the dataset of eddy streamlines.Secondly,the YOLO v5s convolutional neural network is used to train the eddy dataset and to effectively detect mesoscale eddies in the South China Sea region.The experimental results show that the mean precision accuracy of the optimal model obtained after YOLO v5s training reaches 86.10%,which could provide an effective basis for the identification of mesoscale eddies and the construction of 3D structures.Finally,based on the eddy detection results at the same time,the detected eddies at different depths are determined whether they belonged to the same eddy,then the 3D structure of the eddy is built.关键词
中尺度涡/YOLO/三维结构Key words
mesoscale eddies/YOLO/3D structure分类
海洋科学引用本文复制引用
李永,刘格格,杨俊钢,崔伟,焦方涛..基于YOLO算法的海洋中尺度涡三维结构构建[J].数字海洋与水下攻防,2024,7(1):47-53,7.基金项目
国家自然科学重点基金项目"基于海洋表层卫星遥感观测的海洋水下动力环境智能探测方法研究"(62231028). （62231028）
