Unsupervised Multimodal Change Detection Based on Structural Relationship Graph Representation Learning

Unsupervised multimodal change detection is a practical and challenging topic that can play an important role in time-sensitive emergency applications. To address the challenge that multimodal remote sensing images cannot be directly compared due to their modal heterogeneity, we take advantage of tw...

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Vydané v:	arXiv.org
Hlavní autori:	Chen, Hongruixuan, Yokoya, Naoto, Wu, Chen, Du, Bo
Médium:	Paper
Jazyk:	English
Vydavateľské údaje:	Ithaca Cornell University Library, arXiv.org 03.10.2022
Predmet:	Change detection Graph representations Graphical representations Graphs Heterogeneity Image analysis Image filters Learning Remote sensing Similarity
ISSN:	2331-8422
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