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  2. 烟台海岸带研究所
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  4. 中科院海岸带环境过程与生态修复重点实验室
Fuzzy graph convolutional network for hyperspectral image classification

文献类型：期刊论文

作者Xu, Jindong2; Li, Kang2,3; Li, Ziyi2; Chong, Qianpeng2; Xing, Haihua4; Xing, Qianguo1; Ni, Mengying2
刊名ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
出版日期2024
卷号127页码:13
关键词Graph convolutional network Hyperspectral image Image classification Fuzzy logic Graph construction method
ISSN号0952-1976
DOI10.1016/j.engappai.2023.107280
通讯作者Ni, Mengying(nimengying@ytu.edu.cn)
英文摘要-Graph convolutional network (GCN) has attracted much attention in the field of hyperspectral image classification for its excellent feature representation and convolution on arbitrarily structured non-Euclidean data. However, most state-of-the-art methods build a graph utilize the distance measure, which makes it challenging to fully characterize the complex relationship of hyperspectral remote sensing data. Moreover, the hyperspectral image usually has uncertainty introduced by the problems of the spectral variability and noise interference. This article uses fuzzy theory to optimize the GCN and thus solve the uncertainty problem in hyperspectral images, and presents a novel fuzzy graph convolutional network (F-GCN) for hyperspectral image classification. By calculating the fuzzy similarity of samples, a robust graph is first built rather than using the traditional Euclidean distance method, which allows a better representation of the complex relationship between hyperspectral remote sensing data. Furthermore, the proposed network introduces fuzzy layers into the model to cope with the ambiguity of the hyperspectral image. Finally, the classification results for three real-world hyperspectral data sets to show its feasibility and effectiveness in hyperspectral image classification.
WOS研究方向Automation & Control Systems ; Computer Science ; Engineering
语种英语
WOS记录号WOS:001243181100001
资助机构National Natural Science Foundation of China ; Shandong Provincial Natural Science Foundation of China
源URL[http://ir.yic.ac.cn/handle/133337/35968]  
专题烟台海岸带研究所_中科院海岸带环境过程与生态修复重点实验室
烟台海岸带研究所_海岸带信息集成与综合管理实验室
通讯作者Ni, Mengying
作者单位1.Chinese Acad Sci, Yantai Inst Coastal Zone Res, Yantai 264003, Peoples R China
2.Yantai Univ, Sch Comp & Control Engn, Yantai 264005, Peoples R China
3.Quan Cheng Lab, Jinan 250100, Peoples R China
4.Hainan Normal Univ, Coll Informat Sci & Technol, Haikou 571158, Peoples R China
推荐引用方式
GB/T 7714		 Xu, Jindong,Li, Kang,Li, Ziyi,et al. Fuzzy graph convolutional network for hyperspectral image classification[J]. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE,2024,127:13.
APA Xu, Jindong.,Li, Kang.,Li, Ziyi.,Chong, Qianpeng.,Xing, Haihua.,...&Ni, Mengying.(2024).Fuzzy graph convolutional network for hyperspectral image classification.ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE,127,13.
MLA Xu, Jindong,et al."Fuzzy graph convolutional network for hyperspectral image classification".ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 127(2024):13.

入库方式： OAI收割

来源：烟台海岸带研究所

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