基于卷积神经网络的大幅面遥感图像船舶检测与细粒度识别

Jingrun Li, J. Tian, Peng Gao, Linfeng Li
{"title":"基于卷积神经网络的大幅面遥感图像船舶检测与细粒度识别","authors":"Jingrun Li, J. Tian, Peng Gao, Linfeng Li","doi":"10.1109/IGARSS39084.2020.9323246","DOIUrl":null,"url":null,"abstract":"Ship detection and fine-grained recognition in large-format remote sensing image are an important research direction in the field of remote sensing image detection. But less research has been done in this area. Aiming at this problem, this paper constructs a large-format remote sensing image ship target dataset with ship category information, and proposes a background filtering network and a ship fine-grained classification network. The background filtering network is used to quickly filter out the background area, and the ship fine-grained classification network is used to detect ship targets and distinguish ship categories. Compared with the previous method, the method proposed in this paper can significantly improve the efficiency of ship target detection in large-format remote sensing images, while also improving the detection accuracy.","PeriodicalId":444267,"journal":{"name":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Ship Detection and Fine-Grained Recognition in Large-Format Remote Sensing Images Based on Convolutional Neural Network\",\"authors\":\"Jingrun Li, J. Tian, Peng Gao, Linfeng Li\",\"doi\":\"10.1109/IGARSS39084.2020.9323246\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Ship detection and fine-grained recognition in large-format remote sensing image are an important research direction in the field of remote sensing image detection. But less research has been done in this area. Aiming at this problem, this paper constructs a large-format remote sensing image ship target dataset with ship category information, and proposes a background filtering network and a ship fine-grained classification network. The background filtering network is used to quickly filter out the background area, and the ship fine-grained classification network is used to detect ship targets and distinguish ship categories. Compared with the previous method, the method proposed in this paper can significantly improve the efficiency of ship target detection in large-format remote sensing images, while also improving the detection accuracy.\",\"PeriodicalId\":444267,\"journal\":{\"name\":\"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IGARSS39084.2020.9323246\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IGARSS39084.2020.9323246","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

摘要

大幅面遥感图像中的船舶检测与细粒度识别是遥感图像检测领域的一个重要研究方向。但这方面的研究较少。针对这一问题,本文构建了包含船舶类别信息的大幅面遥感图像船舶目标数据集,并提出了背景滤波网络和船舶细粒度分类网络。背景滤波网络用于快速滤除背景区域,船舶细粒度分类网络用于检测船舶目标和区分船舶类别。与以往的方法相比,本文提出的方法可以显著提高大幅面遥感图像中舰船目标的检测效率,同时也提高了检测精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ship Detection and Fine-Grained Recognition in Large-Format Remote Sensing Images Based on Convolutional Neural Network
Ship detection and fine-grained recognition in large-format remote sensing image are an important research direction in the field of remote sensing image detection. But less research has been done in this area. Aiming at this problem, this paper constructs a large-format remote sensing image ship target dataset with ship category information, and proposes a background filtering network and a ship fine-grained classification network. The background filtering network is used to quickly filter out the background area, and the ship fine-grained classification network is used to detect ship targets and distinguish ship categories. Compared with the previous method, the method proposed in this paper can significantly improve the efficiency of ship target detection in large-format remote sensing images, while also improving the detection accuracy.
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
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信