Unsupervised Balanced Hash Codes Learning With Multichannel Feature Fusion | |
Chen, Yaxiong2,3,4; Zhao, Dongjie2,3,4; Lu, Xiongbo2,3,4; Xiong, Shengwu2,3,4; Wang, Huangting1 | |
刊名 | IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING |
2022 | |
卷号 | 15页码:2816-2825 |
关键词 | Feature extraction Codes Data mining Convolution Linear programming Approximation algorithms Semantics Deep hash codes multichannel feature fusion multiscale context information unsupervised hashing learning |
ISSN号 | 1939-1404;2151-1535 |
DOI | 10.1109/JSTARS.2022.3162251 |
产权排序 | 4 |
英文摘要 | Unsupervised hashingalgorithms are widely used in large-scale remote sensing images (RSIs) retrieval task. However, existing RSI retrieval algorithms fail to capture the multichannel characteristic of multispectral RSIs and the balanced property of hash codes, which lead the poor performance of RSI retrieval. To tackle these issues, we develop an unsupervised hashing algorithm, namely, variational autoencoder balanced hashing (VABH), to leverage multichannel feature fusion and multiscale context information to perform RSI retrieval task. First, multichannel feature fusion module is designed to extract RSI feature information by leveraging the multichannel properties of multispectral RSI. Second, multiscale learning module is developed to learn the multiscale context information of RSIs. Finally, a novel objective function is designed to capture the discrimination and balanced property of hash codes in the hashing learning process. Comprehensive experiments on diverse benchmark have well demonstrated the reasonableness and effectiveness of the proposed VABH algorithm. |
语种 | 英语 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
WOS记录号 | WOS:000784198000007 |
内容类型 | 期刊论文 |
源URL | [http://ir.opt.ac.cn/handle/181661/95851] |
专题 | 西安光学精密机械研究所_光学影像学习与分析中心 |
通讯作者 | Xiong, Shengwu |
作者单位 | 1.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Key Lab Spectral Imaging Technol CAS, Xian 710119, Peoples R China 2.Wuhan Univ Technol, Chongqing Res Inst, Chongqing 401122, Peoples R China 3.Wuhan Univ Technol, Sanya Sci & Educ Innovat Pk, Sanya 572000, Peoples R China 4.Wuhan Univ Technol, Sch Comp & Artificial Intelligence, Wuhan 430070, Peoples R China |
推荐引用方式 GB/T 7714 | Chen, Yaxiong,Zhao, Dongjie,Lu, Xiongbo,et al. Unsupervised Balanced Hash Codes Learning With Multichannel Feature Fusion[J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,2022,15:2816-2825. |
APA | Chen, Yaxiong,Zhao, Dongjie,Lu, Xiongbo,Xiong, Shengwu,&Wang, Huangting.(2022).Unsupervised Balanced Hash Codes Learning With Multichannel Feature Fusion.IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,15,2816-2825. |
MLA | Chen, Yaxiong,et al."Unsupervised Balanced Hash Codes Learning With Multichannel Feature Fusion".IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 15(2022):2816-2825. |
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