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基于多尺度下采样的遥感图像目标检测算法

周华平 刘伟东

重庆工商大学学报(自然科学版)2025,Vol.42Issue(4):1-8,8.
重庆工商大学学报(自然科学版)2025,Vol.42Issue(4):1-8,8.DOI:10.16055/j.issn.1672-058X.2025.0004.001

基于多尺度下采样的遥感图像目标检测算法

Remote Sensing Image Object Detection Algorithm Based on Multi-scale Downsampling

周华平 1刘伟东1

作者信息

  • 1. 安徽理工大学计算机科学与工程学院,安徽淮南 232001
  • 折叠

摘要

Abstract

Objective Aiming at the problem of poor detection accuracy of existing remote sensing image object detection algorithms in scenes with large variations of object's scales and complex background information interference,a remote sensing image object detection algorithm,MSD-YOLO(Multi-Scale Downsampling-YOLO)based on multi-scale downsampling,was proposed.Methods Firstly,a multi-scale downsampling(MSD)module was designed,which employed three parallel downsampling branches to extract multi-scale features simultaneously during downsampling.This approach avoided the problem of severe loss of small target feature information after many times of downsampling in existing models.Additionally,an ACON(Activate or Not)activation function with adaptive activation characteristics was introduced to enhance the model's generalization ability.Secondly,the Triplet Attention mechanism was improved,and the Improved Triplet Attention(ITA)mechanism was proposed to adaptively adjust the weight allocation of feature maps by capturing cross-dimensional interactions and emphasizing spatial attention.This mechanism improved the detection performance of the model in scenes with complex background information interference.Results The experimental results showed that the mean average precisions(mAP)of MSD-YOLO on NWPU VHR-10 and RSOD datasets reached 94.9%and 96.8%,respectively,which were both improved by 1.5%compared with the baseline network YOLOv7,and the precisions outperformed those of other classical network models.Conclusion The proposed MSD-YOLO algorithm effectively improves detection accuracy in scenarios with significant scale variations and complex background interference and has valuable applications in remote sensing image object detection scenarios.

关键词

计算机视觉/遥感图像目标检测/MSD-YOLO/YOLOv7/Triplet Attention

Key words

computer vision/remote sensing image object detection/MSD-YOLO/YOLOv7/Triplet Attention

分类

信息技术与安全科学

引用本文复制引用

周华平,刘伟东..基于多尺度下采样的遥感图像目标检测算法[J].重庆工商大学学报(自然科学版),2025,42(4):1-8,8.

基金项目

安徽省重点研发计划国际科技合作专项(202004B11020029). (202004B11020029)

重庆工商大学学报(自然科学版)

1672-058X

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