Unsupervised change detection method in SAR images based on deep belief network using an improved fuzzy C‐means clustering algorithm

Deep learning methods have recently displayed ground‐breaking results for synthetic aperture radar image change detection problem. However, they still face the challenges of intrinsic noise and the difficulty of acquiring labeled data. To sort out these issues, we aim to develop a change detection a...

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Vydané v:	IET image processing Ročník 15; číslo 4; s. 974 - 982
Hlavní autori:	Attioui, Sanae, Najah, Said
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Wiley 01.03.2021
Predmet:	Algebra, set theory, and graph theory Data and information; acquisition, processing, storage and dissemination in geophysics Filtering methods in signal processing Image recognition Instrumentation and techniques for geophysical, hydrospheric and lower atmosphere research Radar theory
ISSN:	1751-9659, 1751-9667
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