电子器件2024，Vol.47Issue(4)：1107-1115,9.DOI:10.3969/j.issn.1005-9490.2024.04.036
基于改进YOLOv4 网络的红外遥感小目标检测方法
Infrared Remote Sensing Small Target Detection Method Based on Improved YOLOv4 Network
摘要
Abstract
Targeting at the poor performance of traditional detection methods for infrared small target,a transferring learning and improved YOLOv4 network based infrared small target detection system is proposed.Firstly,the shallow features extracted by backbone of YOLOv4 network are enhanced,and the difficulty of infrared small target detection is reduced with combination of shallow features and deep features.Secondly,an attention mechanism is introduced to the detection head of YOLOv4 network to help the network focus on infra-red small targets of the feature maps,thus,the background interference to small target detection is reduced.Finally,the transferring learn-ing method is introduced to the training process of YOLOv4 network to solve the problem of lack of labeled training data for infrared small target detection.Experimental results based on public infrared small target detection dataset show that the proposed system improves the detection performance of YOLOv4 network for infrared small target,it also outperforms the other compared detection models.关键词
深度学习/红外遥感/目标检测/迁移学习/深度神经网络/单阶段检测模型Key words
deep learning/infrared remote sensing/target detection/transferring learning/deep neural network/one stage detection model分类
信息技术与安全科学引用本文复制引用
马玉磊,钟潇柔..基于改进YOLOv4 网络的红外遥感小目标检测方法[J].电子器件,2024,47(4):1107-1115,9.基金项目
河南省科技厅重点研发与推广专项(科技攻关)项目(212102210405) （科技攻关）
2022年度新乡学院教育教学改革研究与实践项目成果(31) （31）
