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大尺度遥感图像机场残缺目标识别与评估 认领

Airport target recognition and damage assessment in large-scale remote sensing images
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摘要 针对大尺度遥感中重要特征破损所导致的检测精度低、耗时长等问题,提出了一种基于YOLOv5模型的残缺目标检测与评估方法,弥补了深度网络在残缺目标识别与评估领域的空缺。围绕机场典型区域,构建了以残缺目标为核心的机场目标数据集...展开更多 Aiming at the problem of low detection accuracy and long time due to the damage of important features in largescale remote sensing,this paper proposes a detection and evaluation method of incomplete targets based on YOLOv5 model to make up for the gap in the field of re...MORE Aiming at the problem of low detection accuracy and long time due to the damage of important features in largescale remote sensing,this paper proposes a detection and evaluation method of incomplete targets based on YOLOv5 model to make up for the gap in the field of recognition and evaluation of incomplete targets in deep networks.Firstly,the Airport Target Dataset(ATD)with incomplete target as the core is constructed around the typical area of the airport,and the adaptation of target reasoning is improved based on the YOLOv5 model,the Slice Enhancement Aided Inference Framework(SEAIF)for large-scale remote sensing images is constructed.The experimental results show that the accuracy of incomplete target recognition is more than 90%,and the average processing time of single image is less than 40 s,which is far higher than that of professional interpreters in accuracy and speed.This method is helpful to timely and accurate assessment of airport infrastructure,aid disaster response and maintenance operations,and has important application prospects.FEWER
作者 于淼 宋政伟 张元淳 孙莉 张国和 刘达 YU Miao;SONG Zhengwei;ZHANG Yuanchun;SUN Li;ZHANG Guohe;LIU Da(School of Microelectronics,Department of Electronics and Information,Xi′an Jiaotong University,Xi′an 710077,China;School of Aeronautical Engineering,Air Force Engineering University,Xi′an 710038,China)
机构地区 西安交通大学微电子学院 中国人民解放军空军工程大学航空工程学院
出处 《微电子学与计算机》 2025年第4期16-27,共12页 Microelectronics & Computer
基金 陕西省重点产业创新链(群)-工业领域(2022ZDLGY06-02)。
关键词 大尺度图像 残缺目标识别 机场目标数据集 YOLOv5 large-scale image damaged target recognition airport target dataset YOLOv5
分类号 TP751 [自动化与计算机技术—检测技术与自动化装置] V35 [自动化与计算机技术—控制科学与工程] E91 [航空宇航科学与技术—人机与环境工程]
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微电子学与计算机
2025年 第4期
科创助手
论文智评
维普砚承
维普斟知

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