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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Bibliographic Details

Published in:	arXiv.org
Main Authors:	Chen, Hongruixuan, Yokoya, Naoto, Wu, Chen, Du, Bo
Format:	Paper
Language:	English
Published:	Ithaca Cornell University Library, arXiv.org 03.10.2022
Subjects:	Change detection Graph representations Graphical representations Graphs Heterogeneity Image analysis Image filters Learning Remote sensing Similarity
ISSN:	2331-8422
Online Access:	Get full text
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