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Feature extraction based on tensor modelling for classification methods
Yan, Ronghua1,3; Peng, Jinye1,2; Ma, Dongmei4; Wen, Desheng3; Dong, Yingdi5
2018-01-09
会议名称2017 International Conference on the Frontiers and Advances in Data Science, FADS 2017
会议录名称Conference Proceedings - 2017 International Conference on the Frontiers and Advances in Data Science, FADS 2017
卷号2018-January
页码102-107
会议日期2017-10-23
会议地点Xian, China
出版者Institute of Electrical and Electronics Engineers Inc.
产权排序1
摘要

Both spatial and spectral information is used when a hyperspectral image is modeled as a tensor. However, this model does not consider both the class and within-class information about the spectral features of ground objects. This means that further improving classification is very difficult. The authors propose that class information, within-class information, and pixels are selected to model a third-order tensor. The most important advantage of the proposed method is that all the pixels of one class are mapped to the same coefficient vector. Therefore, the within-class scatter is minimized, and the classification is improved when compared to the previous methods. © 2017 IEEE.

作者部门空间光学应用研究室
DOI10.1109/FADS.2017.8253205
收录类别EI
ISBN号9781538631485
语种英语
EI入藏号20183005592134
EI主题词Extraction ; Feature Extraction ; Pixels ; Remote Sensing ; Spectroscopy ; Tensors
EI分类号Electronics And Communication Engineering::Electronic Equipment, Radar, Radio And Television::Information & Communication Theory
引用统计
文献类型会议论文
条目标识符http://ir.opt.ac.cn/handle/181661/30525
专题空间光学应用研究室
通讯作者Yan, Ronghua
作者单位1.School of Electronics and Information, Northwestern Polytechnical University, Xi'an, China;
2.School of Information and Technology, Northwest University, Xi'an, China;
3.Xi'an Institute of Optics and Precision Mechanics, CAS, Xi'an, China;
4.Xi'an-Janssen Pharmaceutical Ltd., Xi'an, China;
5.School of Information and Control Engineering, Xi'an University of Architecture and Technology, Xi'an, China
推荐引用方式
GB/T 7714
Yan, Ronghua,Peng, Jinye,Ma, Dongmei,et al. Feature extraction based on tensor modelling for classification methods[C]:Institute of Electrical and Electronics Engineers Inc.,2018:102-107.
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