EMS-GCN: An End-to-End Mixhop Superpixel-Based Graph Convolutional Network for Hyperspectral Image Classification
Author:
Affiliation:
1. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China
Funder
National Natural Science Foundation of China
Natural Science Foundation of Hubei Province
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Earth and Planetary Sciences,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/36/9633014/09745164.pdf?arnumber=9745164
Reference57 articles.
1. Nonlocal Graph Convolutional Networks for Hyperspectral Image Classification
2. Spectral–Spatial Graph Convolutional Networks for Semisupervised Hyperspectral Image Classification
3. Visual Attention-Driven Hyperspectral Image Classification
4. Residual Spectral–Spatial Attention Network for Hyperspectral Image Classification
5. Learning to Pay Attention on Spectral Domain: A Spectral Attention Module-Based Convolutional Network for Hyperspectral Image Classification
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