S3Net: Spectral–Spatial Siamese Network for Few-Shot Hyperspectral Image Classification-Reference-Cited by-同舟云学术

S3Net: Spectral–Spatial Siamese Network for Few-Shot Hyperspectral Image Classification

Published:2022 Issue: Volume:60 Page:1-19
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Xue Zhaohui¹^ORCID,Zhou Yiyang¹^ORCID,Du Peijun²^ORCID

Affiliation:

1. School of Earth Sciences and Engineering and the Jiangsu Province Engineering Research Center of Water Resources and Environment Assessment Using Remote Sensing, Hohai University, Nanjing, China

2. Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, the Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, and the School of Geography and Ocean Science, Nanjing University, Nanjing, China

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/9633014/09791365.pdf?arnumber=9791365

Reference48 articles.

1. Deep Cross-Domain Few-Shot Learning for Hyperspectral Image Classification

2. Sensor-Independent Hyperspectral Target Detection With Semisupervised Domain Adaptive Few-Shot Learning