Spatial refinement based method for small-sized target detection

被引：0

作者：

Yu, Wei ^{[1
]}

Guo, Yang ^{[2
]}

Lin, Di ^{[3
]}

Chang, He ^{[3
]}

机构：

[1] Southwest China Inst Elect Technol, Dept Space, Yingkang West Ave, Chengdu, Sichuan, Peoples R China

[2] PLA Acad Mil Sci, Res Inst, 10091, Beijing, Peoples R China

[3] Univ Elect Sci & Technol China, Dept Informat & Software Engn, Xiyuan Ave, Chengdu 611731, Sichuan, Peoples R China

来源：

WIRELESS NETWORKS | 2024年 / 30卷 / 07期

关键词：

Target detection; Long-distance images; Small-sized targets;

D O I：

10.1007/s11276-023-03403-8

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

To detect small-sized targets in long-distance images, we propose a spatial refinement-based method by fusing features of small-sized targets. Specifically, we add a spatial refinement module (SRM) into the structure of FPN to detect small-sized targets. The redundancy, blur, and inaccuracy that appear in fusion improve the accuracy of the detection model. The simulation results show that the combination of SRM and FPN outperforms the other benchmark detection methods on small-sized targets.

引用

页码：6481 / 6492

页数：12

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