Few-Shot Hyperspectral Image Classification Based on Adaptive Subspaces and Feature Transformation-Reference-Cited by-同舟云学术

Few-Shot Hyperspectral Image Classification Based on Adaptive Subspaces and Feature Transformation

Published:2022 Issue: Volume:60 Page:1-17
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,Huang Shaojie¹^ORCID,Xiao Zhu²^ORCID,Li Xianmin¹,Zhu Yongdong³^ORCID,Regan Amelia C.⁴^ORCID,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 Electronic Engineering, Hunan University, Changsha, China

3. Zhejiang Laboratory, Hangzhou, China

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

Funder

National Natural Science Foundation of China

Science and Technology on Communication Information Security Control Laboratory

Funding Project of the Zhejiang Laboratory

Key Research and Development Project of Hunan Province of China

Science and Technology Project of the Hunan Provincial Water Resources Department

Scientific Research Project of the Department of the Natural Resources

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/9633014/09709262.pdf?arnumber=9709262

Reference43 articles.

1. Learning Sensor-Specific Spatial-Spectral Features of Hyperspectral Images via Convolutional Neural Networks

2. Learning and Transferring Deep Joint Spectral–Spatial Features for Hyperspectral Classification

3. Global Prototypical Network for Few-Shot Hyperspectral Image Classification

4. A Spatial–Spectral Prototypical Network for Hyperspectral Remote Sensing Image

5. Deep Induction Network for Small Samples Classification of Hyperspectral Images

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