Soft Instance-Level Domain Adaptation With Virtual Classifier for Unsupervised Hyperspectral Image Classification-Reference-Cited by-同舟云学术

Soft Instance-Level Domain Adaptation With Virtual Classifier for Unsupervised Hyperspectral Image Classification

Published:2023 Issue: Volume:61 Page:1-13
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,Chen Yang¹,Kong Yi¹^ORCID,Wang Xuesong¹^ORCID

Affiliation:

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

Funder

National Natural Science Foundation of China

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/ielx7/36/10006360/10102293.pdf?arnumber=10102293

Reference39 articles.

1. Topological Structure and Semantic Information Transfer Network for Cross-Scene Hyperspectral Image Classification

2. Joint Correlation Alignment-Based Graph Neural Network for Domain Adaptation of Multitemporal Hyperspectral Remote Sensing Images

3. Hyperspectral Anomaly Detection: A Dual Theory of Hyperspectral Target Detection

4. An Unsupervised Domain Adaptation Method Towards Multi-Level Features and Decision Boundaries for Cross-Scene Hyperspectral Image Classification

5. Domain Adaptation Based on Graph and Statistical Features for Cross-Scene Hyperspectral Image Classification

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