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基于深度学习航拍图像检测的梯度聚类算法

Gradient Clustering Algorithm Based on Deep Learning Aerial Image Detection

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摘要

针对在目标检测中现有方法检测速度慢的问题,基于航拍图像中人造物体含有大量边缘的特点,提出了一种基于梯度聚类的区域建议算法(APM)。利用目标检测算法对提取的感兴趣区域进行检测,在DOTA (Dataset for Object deTection in Aerial Images)数据集上对算法的实时性和准确率进行了测试。研究结果表明,所提算法极大地提升了目标检测算法对大尺寸、目标密集的航拍图像的检测速度,该方法的召回率较高。

Abstract

An algorithm called gradient clustering based area proposal method (APM) is proposed to solve the problem that the existing methods are slow to detect objects, which is based on a large number of edges of artificial objects in aerial images. Then the extracted regions of interest are detected by the object detection method. The real-time performance and precision rate of this method are evaluated on the DOTA (Dataset for Object Detection in Aerial Images). The research results show that the proposed method greatly improves the detection speed of large-size, target-dense aerial images by the object detection algorithm, and still keeps a high recall rate.

Newport宣传-MKS新实验室计划
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中图分类号:TP751.1

DOI:10.3788/lop56.061007

所属栏目:图像处理

基金项目:国家自然科学基金(61271376)

收稿日期:2018-08-17

修改稿日期:2018-09-20

网络出版日期:2018-10-12

作者单位    点击查看

解博:国防科技大学脉冲功率激光技术国家重点实验室, 安徽 合肥 230037
朱斌:国防科技大学脉冲功率激光技术国家重点实验室, 安徽 合肥 230037
张宏伟:国防科技大学脉冲功率激光技术国家重点实验室, 安徽 合肥 230037
马旗:国防科技大学脉冲功率激光技术国家重点实验室, 安徽 合肥 230037
张扬:国防科技大学脉冲功率激光技术国家重点实验室, 安徽 合肥 230037

联系人作者:解博(bigboo@foxmail.com)

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引用该论文

Xie Bo,Zhu Bin,Zhang Hongwei,Ma Qi,Zhang Yang. Gradient Clustering Algorithm Based on Deep Learning Aerial Image Detection[J]. Laser & Optoelectronics Progress, 2019, 56(6): 061007

解博,朱斌,张宏伟,马旗,张扬. 基于深度学习航拍图像检测的梯度聚类算法[J]. 激光与光电子学进展, 2019, 56(6): 061007

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