无线互联科技2024,Vol.21Issue(10) :40-42.

基于改进YOLOv5的红外目标检测

Infrared target detection based on improved YOLOv5

陈超峰 赵阳 朱盛滔
无线互联科技2024,Vol.21Issue(10) :40-42.

基于改进YOLOv5的红外目标检测

Infrared target detection based on improved YOLOv5

陈超峰 1赵阳 1朱盛滔1
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作者信息

  • 1. 西京学院,陕西 西安 710123
  • 折叠

摘要

针对红外成像特性及其应用环境的差异导致的红外目标检测准确性不足等问题,文章提出了一种基于改进YOLOv5 算法的红外目标检测方法.该方法引入了SIoU损失函数和多尺度扩张注意力机制,以增强模型对小尺寸目标和复杂背景中目标的检测性能.实验结果表明,与未改进的YOLOv5 模型相比,改进模型在精确率、召回率和平均精确率等关键性能指标上均有显著提升,证明了该改进方法的有效性.

Abstract

Aiming at the problems of insufficient accuracy of infrared target detection caused by differences in infrared imaging characteristics and their application environments,this paper proposes an infrared target detection method based on the improved YOLOv5 algorithm.The method introduces the SIoU loss function and the multi-scale expansion attention mechanism to enhance the model's detection performance for small-size targets and targets in complex backgrounds.The experimental results show that compared with the unimproved YOLOv5 model,the improved model has significant improvement in key performance indicators such as precision rate,recall rate and average precision rate,which proves the effectiveness of the improved method.

关键词

红外目标检测/SIoU损失函数/多尺度扩张注意力

Key words

infrared target detection/SIoU loss function/multiscale dilated attention

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出版年

2024
无线互联科技
江苏省科学技术情报研究所

无线互联科技

影响因子:0.263
ISSN:1672-6944
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