海洋测绘2024，Vol.44Issue(3)：78-82,5.DOI:10.3969/j.issn.1671-3044.2024.03.016
基于样本重构的船舶小目标检测算法研究
Research on tiny ship detection algorithm based on sample reconstruction
摘要
Abstract
Aiming at the problems of small ship target scale,uneven scene distribution,small proportion of target size relative to sample size and poor generalization performance of deep learning model for small targets in remote sensing images,a sample reconstruction method is proposed.Firstly,the ship target is cut according to its smallest circumscribed rectangle,and then a standard size sample is synthesized in various ways.Through sample reconstruction,the proportion of targets in the sample can be increased,and the problem of uneven distribution of targets in different scenarios can be solved.The experiment found that the model trained by the sample reconstruction method has improved the detection ability of small targets.Combined with adding a small target detection layer to the network,the results show that the Average Precision(AP)of the model on the test sample arising from 0.502 to 0.674,verifying the effectiveness of the method.关键词
船舶检测/小目标检测/样本重构/深度学习/旋转目标Key words
ship detection/small object detection/sample reconstruction/deep learning/oriented object分类
天文与地球科学引用本文复制引用
吴祖勇,朱济帅,邓美环,陈木森,徐开..基于样本重构的船舶小目标检测算法研究[J].海洋测绘,2024,44(3):78-82,5.基金项目
国家重点研发计划(2021YFC3101802) （2021YFC3101802）
2022年海口市重点科技计划项目(2022-022). （2022-022）
