Global–Local 3-D Convolutional Transformer Network for Hyperspectral Image Classification-Reference-Cited by-同舟云学术

Global–Local 3-D Convolutional Transformer Network for Hyperspectral Image Classification

Published:2023 Issue: Volume:61 Page:1-20
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Qi Wenchao¹^ORCID,Huang Changping¹,Wang Yibo¹^ORCID,Zhang Xia¹,Sun Weiwei²^ORCID,Zhang Lifu¹^ORCID

Affiliation:

1. National Engineering Research Center of Satellite Remote Sensing Applications, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China

2. Department of Geography and Spatial Information Techniques, Ningbo University, Ningbo, China

Funder

Youth Innovation Promotion Association, CAS

Key Research Program of Frontier Sciences, Chinese Academy of Sciences

Common Application Support Platform for Land Observation Satellites of China’s Civil Space Infrastructure under Grant CASPLOS_CCSI

Science and Technology Project for Black Soil Granary

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/10006360/10115325.pdf?arnumber=10115325

Reference55 articles.

1. Deep Feature Extraction and Classification of Hyperspectral Images Based on Convolutional Neural Networks

2. Semisupervised Hyperspectral Image Classification Based on Generative Adversarial Networks

3. Spectral–Spatial Residual Network for Hyperspectral Image Classification: A 3-D Deep Learning Framework

4. Hyperspectral Image Classification Based on a 3D Octave Convolution and 3D Multiscale Spatial Attention Network

5. Three-dimensional convolutional neural network model for tree species classification using airborne hyperspectral images

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