现代电子技术2024，Vol.47Issue(7)：49-53,5.DOI:10.16652/j.issn.1004-373x.2024.07.008
基于RSSD的遥感图像目标检测算法
RSSD-based object detection algorithm for remote sensing image
吕向东 1彭超亮 2陈治国 2孙鹏飞 1赵晓楠 1徐旸2
作者信息
- 1. 山东港口青岛港集团有限公司,山东 青岛 266001
- 2. 中车长江运输设备集团有限公司,湖北 武汉 430065
- 折叠
摘要
Abstract
In view of the fact that SSD(signal shot multibox detector)algorithm is prone to missing inspection and has low detection accuracy when detecting remote sensing image objects,a remote sensing image object detection algorithm based on residual SSD network is proposed.On the basis of the SSD network structure,the benchmark network model VGG is replaced with the residual network model ResNet-50.By increasing the network depth,the underlying features of the small object data set of remote sensing images are extracted sufficiently,and the attention module is introduced to make the receptive field pay more attention to the object features and enhance the information representation ability of the low-level network.The feature pyramid fusion method is used to integrate the high-level semantic features and low-level visual features of the network structure,so as to enhance the localization ability of the detection objects.Experimental results show that the proposed algorithm enhances the interference suppression of complex background,and improves the detection accuracy of small objects.Therefore,it has better detection performance than the traditional SSD algorithm.关键词
SSD/残差网络/注意力模块/金字塔融合/遥感图像/小目标/高层语义特征/低层视觉特征Key words
SSD/residual network/attention module/pyramid fusion/remote sensing image/small object/high-level semantic feature/low-level visual feature分类
电子信息工程引用本文复制引用
吕向东,彭超亮,陈治国,孙鹏飞,赵晓楠,徐旸..基于RSSD的遥感图像目标检测算法[J].现代电子技术,2024,47(7):49-53,5.
