Causal Meta-Transfer Learning for Cross-Domain Few-Shot Hyperspectral Image Classification-Reference-Cited by-同舟云学术

Causal Meta-Transfer Learning for Cross-Domain Few-Shot Hyperspectral Image Classification

Published:2023 Issue: Volume:61 Page:1-14
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Cheng Yuhu¹^ORCID,Zhang Wei¹^ORCID,Wang Haoyu¹,Wang Xuesong¹^ORCID

Affiliation:

1. Engineering Research Center of Intelligent Control for Underground Space, Ministry of Education, and the School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province

Excellent Post-Doctorate Program of Jiangsu Province

Key Research and Development Program of Jiangsu Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/10006360/10231133.pdf?arnumber=10231133

Reference49 articles.

1. Hyperspectral and LiDAR Data Classification Based on Structural Optimization Transmission

2. SpectralFormer: Rethinking Hyperspectral Image Classification with Transformers

3. Hyperspectral Image Transformer Classification Networks

4. Semi-Supervised Locality Preserving Dense Graph Neural Network With ARMA Filters and Context-Aware Learning for Hyperspectral Image Classification

5. Unsupervised Self-Correlated Learning Smoothy Enhanced Locality Preserving Graph Convolution Embedding Clustering for Hyperspectral Images

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