A Self-Supervised-Driven Open-Set Unsupervised Domain Adaptation Method for Optical Remote Sensing Image Scene Classification and Retrieval
Author:
Affiliation:
1. School of Geosciences and Info-Physics, Central South University, Changsha, China
2. School of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan, China
Funder
National Natural Science Foundation of China
Hunan Provincial Natural Science Foundation of China
Shandong Provincial Natural Science Foundation
Yunnan Fundamental Research Projects
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Earth and Planetary Sciences,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/36/10006360/10078892.pdf?arnumber=10078892
Reference77 articles.
1. Domain Adaptation Based on Correlation Subspace Dynamic Distribution Alignment for Remote Sensing Image Scene Classification
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4. Cycle self-training for domain adaptation;liu;Proc Adv Neural Inf Process Syst,2021
5. Two novel benchmark datasets from ArcGIS and bing world imagery for remote sensing image retrieval
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