基于深度学习的遥感图像目标检测算法综述

Zhe Zheng, Lin Lei, Hao Sun, Gangyao Kuang
{"title":"基于深度学习的遥感图像目标检测算法综述","authors":"Zhe Zheng, Lin Lei, Hao Sun, Gangyao Kuang","doi":"10.1109/ICIVC50857.2020.9177453","DOIUrl":null,"url":null,"abstract":"Object detection is an important part of remote sensing image analysis. With the development of the earth observation technology and convolutional neural network, remote sensing image object detection technology based on deep learning has received more and more attention and research. At present, many excellent object detection algorithms have been proposed and applied in the field of remote sensing. In this paper, the object detection algorithms of remote sensing image is systematically summarized, the main contents include the traditional remote sensing image object detection method and the method based on deep learning, emphasis on summarize the remote sensing image object detection algorithm based on deep learning and its development course, then we introduced the rule of performance evaluation of object detection and datasets that commonly used. Finally, the future development trend is analyzed and prospected. It is hoped that this summary and analysis can provide some reference for future research on object detection technology in remote sensing field.","PeriodicalId":6806,"journal":{"name":"2020 IEEE 5th International Conference on Image, Vision and Computing (ICIVC)","volume":"4 1","pages":"34-43"},"PeriodicalIF":0.0000,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"A Review of Remote Sensing Image Object Detection Algorithms Based on Deep Learning\",\"authors\":\"Zhe Zheng, Lin Lei, Hao Sun, Gangyao Kuang\",\"doi\":\"10.1109/ICIVC50857.2020.9177453\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Object detection is an important part of remote sensing image analysis. With the development of the earth observation technology and convolutional neural network, remote sensing image object detection technology based on deep learning has received more and more attention and research. At present, many excellent object detection algorithms have been proposed and applied in the field of remote sensing. In this paper, the object detection algorithms of remote sensing image is systematically summarized, the main contents include the traditional remote sensing image object detection method and the method based on deep learning, emphasis on summarize the remote sensing image object detection algorithm based on deep learning and its development course, then we introduced the rule of performance evaluation of object detection and datasets that commonly used. Finally, the future development trend is analyzed and prospected. It is hoped that this summary and analysis can provide some reference for future research on object detection technology in remote sensing field.\",\"PeriodicalId\":6806,\"journal\":{\"name\":\"2020 IEEE 5th International Conference on Image, Vision and Computing (ICIVC)\",\"volume\":\"4 1\",\"pages\":\"34-43\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE 5th International Conference on Image, Vision and Computing (ICIVC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIVC50857.2020.9177453\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 5th International Conference on Image, Vision and Computing (ICIVC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIVC50857.2020.9177453","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12

摘要

目标检测是遥感图像分析的重要组成部分。随着对地观测技术和卷积神经网络的发展,基于深度学习的遥感图像目标检测技术得到了越来越多的关注和研究。目前,已有许多优秀的目标检测算法被提出并应用于遥感领域。本文对遥感图像的目标检测算法进行了系统的总结,主要内容包括传统的遥感图像目标检测方法和基于深度学习的遥感图像目标检测方法,重点总结了基于深度学习的遥感图像目标检测算法及其发展历程,然后介绍了目标检测性能评价规则和常用的数据集。最后,对未来的发展趋势进行了分析和展望。希望本文的总结和分析能够为今后遥感领域目标检测技术的研究提供一些参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
A Review of Remote Sensing Image Object Detection Algorithms Based on Deep Learning
Object detection is an important part of remote sensing image analysis. With the development of the earth observation technology and convolutional neural network, remote sensing image object detection technology based on deep learning has received more and more attention and research. At present, many excellent object detection algorithms have been proposed and applied in the field of remote sensing. In this paper, the object detection algorithms of remote sensing image is systematically summarized, the main contents include the traditional remote sensing image object detection method and the method based on deep learning, emphasis on summarize the remote sensing image object detection algorithm based on deep learning and its development course, then we introduced the rule of performance evaluation of object detection and datasets that commonly used. Finally, the future development trend is analyzed and prospected. It is hoped that this summary and analysis can provide some reference for future research on object detection technology in remote sensing field.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Online Multi-object Tracking with Siamese Network and Optical Flow Research on Product Style Design Based on Genetic Algorithm Super-Resolution Reconstruction Algorithm of Target Image Based on Learning Background Air Quality Inference with Deep Convolutional Conditional Random Field Feature Point Extraction and Matching Method Based on Akaze in Illumination Invariant Color Space
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1