航空学报2026，Vol.47Issue(10)：49-62,14.DOI:10.7527/S1000-6893.2025.32599
基于混合专家模型的航天遥感图像目标检测
Spaceborne remote sensing image object detection based on mixture of experts model
摘要
Abstract
As an important application direction in the field of spaceborne remote sensing,object detection is of great significance in disaster emergency response,resource management,environmental monitoring and other fields.We take ship targets as an example to study object detection in spaceborne remote sensing images.Spaceborne remote sensing covers sea areas in different regions worldwide,and these sea areas have significant differences in geomor-phic features.Existing ship target detection methods mostly use a unified structure to handle different scenarios,mak-ing it difficult to adapt to changes in ground object features in different regions and with different resolutions.To ad-dress this,we introduce the Mixture of Experts(MoE)model into the task of spaceborne remote sensing image object detection,and propose a spaceborne remote sensing image object detection model based on the Mixture of Experts model.It adaptively selects corresponding expert processing for the differential features of different geographical re-gions to achieve more accurate ship target detection in different sea areas.The model includes two groups of experts:one group is guided by spatial resolution information to capture differences in ground object scales under different reso-lutions;the other group uses latitude and longitude information for guidance to adapt to the distribution characteristics of ground objects in different geographical regions.Through the collaborative work of the two groups of experts,the model can more accurately perceive and locate ship targets in images,significantly improving detection performance.In addition,we construct a dataset containing multi-resolution information and latitude and longitude information-the Geographic In-formation Ship Detection Dataset(GISD)to provide data support for the research.We conduct experi-mental verification on the GISD dataset and the public dataset LEVIR-ship.The average precision AP50 of the pro-posed method reaches 80.6%and 85.7%respectively,which is 3.8%and 2.0%higher than that of the best-performing models on the two datasets.关键词
遥感图像/舰船检测/光学遥感/地理信息/混合专家Key words
remote-sensing image/ship detection/optical remote sensing/geographical information/mixture of experts分类
航空航天引用本文复制引用
卢光宇,陈博文,陈科研,邹征夏,史振威..基于混合专家模型的航天遥感图像目标检测[J].航空学报,2026,47(10):49-62,14.基金项目
国家自然科学基金(62125102,U24B20177) National Natural Science Foundation of China(62125102,U24B20177) （62125102,U24B20177）
