干旱区生态环境知识资源中心(Arid): Attribute-Cooperated Convolutional Neural Network for Remote Sensing Image Classification

Arid

DOI	10.1109/TGRS.2020.2987338
	Attribute-Cooperated Convolutional Neural Network for Remote Sensing Image Classification
	Zhang, Yuanlin; Zheng, Xiangtao; Yuan, Yuan; Lu, Xiaoqiang
通讯作者	Zheng, XT
来源期刊	IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
ISSN	0196-2892
EISSN	1558-0644
出版年	2020
卷号	58 期号:12 页码:8358-8371
英文摘要	Remote sensing image (RSI) classification is one of the most important fields in RSI processing. It is well known that RSIs are very complicated due to its various kinds of contents. Therefore, it is very difficult to distinguish different scene categories with similar visual contents, like desert and bare land. To address hard negative categories, an attribute-cooperated convolutional neural network (ACCNN) is proposed to exploit attributes as additional guiding information. First, the classification branch extracts convolutional neural network feature, which is then utilized to recognize the RSI scene categories. Second, the attribute branch is proposed to make the network distinguish scene categories efficiently. The proposed attribute branch shares feature extraction layers with the classification branch and makes the classification branch aware of extra attribute information. Finally, the relationship branch constraints the relationship between the classification branch and the attribute branch. To exploit the attribute information, three attribute-classification data sets are generated (AC-AID, AC-UCM, and AC-Sydney). Experimental results show that the proposed method is competitive to state-of-the-art methods. The data sets are available at https://github.com/CrazyStoneonRoad/Attribute-Cooperated-Classification-Data sets.
英文关键词	Feature extraction Task analysis Convolutional neural networks Remote sensing Visualization Semantics Manuals Attribute learning convolutional neural networks (CNNs) relationship learning remote sensing image (RSI) classification
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000594389800009
WOS关键词	SCENE CLASSIFICATION ; FEATURES ; REPRESENTATION ; SCALE
WOS类目	Geochemistry & Geophysics ; Engineering, Electrical & Electronic ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向	Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/327778
作者单位	[Zhang, Yuanlin; Zheng, Xiangtao; Lu, Xiaoqiang] Chinese Acad Sci, Xian Inst Opt & Precis Mech, Key Lab Spectral Imaging Technol CAS, Xian 710119, Peoples R China; [Zhang, Yuanlin] Univ Chinese Acad Sci, Beijing 100049, Peoples R China; [Yuan, Yuan] Northwestern Polytech Univ, Ctr Opt Imagery Anal & Learning, Sch Comp Sci, Xian 710072, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Yuanlin,Zheng, Xiangtao,Yuan, Yuan,et al. Attribute-Cooperated Convolutional Neural Network for Remote Sensing Image Classification[J],2020,58(12):8358-8371.
APA	Zhang, Yuanlin,Zheng, Xiangtao,Yuan, Yuan,&Lu, Xiaoqiang.(2020).Attribute-Cooperated Convolutional Neural Network for Remote Sensing Image Classification.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,58(12),8358-8371.
MLA	Zhang, Yuanlin,et al."Attribute-Cooperated Convolutional Neural Network for Remote Sensing Image Classification".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 58.12(2020):8358-8371.