Hyperspectral Image Classification Based on Superpixel Feature Subdivision and Adaptive Graph Structure-Reference-Cited by-同舟云学术

Hyperspectral Image Classification Based on Superpixel Feature Subdivision and Adaptive Graph Structure

Published:2022 Issue: Volume:60 Page:1-15
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Bai Jing¹^ORCID,Shi Wei¹,Xiao Zhu²^ORCID,Regan Amelia C.³^ORCID,Ali Talal Ahmed Ali²,Zhu Yongdong⁴^ORCID,Zhang Rui⁵,Jiao Licheng¹^ORCID

Affiliation:

1. Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi’an, China

2. College of Computer Science and Electronics Engineering, Hunan University, Changsha, China

3. Department of Computer Science, Institute of Transportation Studies, University of California, Irvine, CA, USA

4. Zhejiang Laboratory, Hangzhou, China

5. Hubei Key Laboratory of Transportation Internet of Things, School of Computer Science and Technology, Wuhan University of Technology, Wuhan, China

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Science and Technology Project of Hunan Provincial Water Resources Department

Scientific Research Project of Department of the Natural Resources of Hunan Province

Fund of National Key Laboratory of Science and Technology on Remote Sensing Information and Imagery Analysis

Science and Technology on Communication Information Security Control Laboratory

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/9633014/09718246.pdf?arnumber=9718246

Reference53 articles.

1. Semi-supervised classification with graph convolutional networks;kipf;arXiv 1609 02907,2016

2. Caps-TripleGAN: GAN-Assisted CapsNet for Hyperspectral Image Classification

3. Attention is all you need;vaswani;Proc Adv Neural Inf Process Syst,2017

4. Spatial Sequential Recurrent Neural Network for Hyperspectral Image Classification

5. Cascaded Recurrent Neural Networks for Hyperspectral Image Classification

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