Cross-Domain Few-Shot Hyperspectral Image Classification With Cross-Modal Alignment and Supervised Contrastive Learning-Reference-Cited by-同舟云学术

Cross-Domain Few-Shot Hyperspectral Image Classification With Cross-Modal Alignment and Supervised Contrastive Learning

Published:2024 Issue: Volume:62 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:

Li Zhaokui¹^ORCID,Zhang Chenyang¹,Wang Yan¹,Li Wei²^ORCID,Du Qian³^ORCID,Fang Zhuoqun⁴^ORCID,Chen Yushi⁵^ORCID

Affiliation:

1. School of Computer Science, Shenyang Aerospace University, Shenyang, China

2. School of Information and Electronics and the Beijing Key Laboratory of Fractional Signals and Systems, Beijing Institute of Technology, Beijing, China

3. Department of Electrical and Computer Engineering, Mississippi State University, Starkville, MS, USA

4. College of Artificial Intelligence, Shenyang Aerospace University, Shenyang, China

5. School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin, China

Funder

National Natural Science Foundation of China

Applied Basic Research Project of Liaoning Province

Fundamental Research Funds for the Universities of Liaoning Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/36/10354519/10542106.pdf?arnumber=10542106

Reference58 articles.

1. Supervised Classification of Remotely Sensed Imagery Using a Modified $k$-NN Technique

2. Classification of hyperspectral remote sensing images with support vector machines

3. Classification of hyperspectral data from urban areas based on extended morphological profiles

4. Three-Dimensional Gabor Wavelets for Pixel-Based Hyperspectral Imagery Classification

5. Recent Advances on Spectral–Spatial Hyperspectral Image Classification: An Overview and New Guidelines

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Super-Resolution Image Reconstruction Method between Sentinel-2 and Gaofen-2 Based on Cascaded Generative Adversarial Networks;Applied Sciences;2024-06-08