Prototype-Based Pseudo-Label Refinement for Semi-Supervised Hyperspectral Image Classification-Reference-Cited by-同舟云学术

Prototype-Based Pseudo-Label Refinement for Semi-Supervised Hyperspectral Image Classification

Published:2024 Issue: Volume:21 Page:1-5
ISSN:1545-598X
Container-title:IEEE Geoscience and Remote Sensing Letters
language:
Short-container-title:IEEE Geosci. Remote Sensing Lett.

Author:

Chen Renyi¹^ORCID,Yao Huaxiong¹^ORCID,Chen Wenjing²^ORCID,Sun Hao¹^ORCID,Xie Wei¹^ORCID,Dong Le³^ORCID,Lu Xiaoqiang⁴^ORCID

Affiliation:

1. Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning, the School of Computer Science, and the National Language Resources Monitoring and Research Center for Network Media, Central China Normal University, Wuhan, China

2. School of Computer Science, Hubei University of Technology, Wuhan, China

3. School of Artificial Intelligence, Xidian University, Xi’an, China

4. College of Physics and Information Engineering, Fuzhou University, Fuzhou, China

Funder

National Natural Science Foundation of China

Hubei Provincial Natural Science Foundation of China

Knowledge Innovation Program of Wuhan-Shuguang Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/8859/10365397/10491298.pdf?arnumber=10491298

Reference18 articles.

1. Deep Quadruple-Based Hashing for Remote Sensing Image-Sound Retrieval

2. Deep Cross-Modal Image–Voice Retrieval in Remote Sensing

3. Semisupervised Cross-Scale Graph Prototypical Network for Hyperspectral Image Classification

4. MATNet: A Combining Multi-Attention and Transformer Network for Hyperspectral Image Classification

5. SpectralFormer: Rethinking Hyperspectral Image Classification with Transformers