Evaluation of the change in synthetic aperture radar imaging using transfer learning and residual network

Evaluation of the change in synthetic aperture radar imaging using transfer learning and residual network

Change detection from synthetic aperture radar images becomes a key technique to detect change area related to some phenomenon as flood and deformation of the earth surface. This paper proposes a transfer learning and Residual Network with 18 layers (ResNet-18) architecture-based method for change d...

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Bibliographic Details
Main Authors: I. Hamdi, Y. Tounsi, M. Benjelloun, A. Nassim
Format: Article
Language:English
Published: Samara National Research University 2021-07-01
Series:Компьютерная оптика
Subjects:
sar images
change detection
transfer learning
residual network
Online Access:http://computeroptics.ru/eng/KO/Annot/KO45-4/450415e.html

Internet

http://computeroptics.ru/eng/KO/Annot/KO45-4/450415e.html

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