Self-Supervised Feature Representation for SAR Image Target Classification Using Contrastive Learning

Self-Supervised Feature Representation for SAR Image Target Classification Using Contrastive Learning

Nowadays, the developed deep neural networks (DNNs) have been widely applied to synthetic aperture radar (SAR) image interpretation, such as target classification and recognition, which can automatically learn high-level semantic features in data-driven and task-driven manners. For the supervised le...

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Bibliographic Details
Main Authors: Hao Pei, Mingjie Su, Gang Xu, Mengdao Xing, Wei Hong
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Contrastive learning (CL)
convolutional neural network (CNN)
self-supervised repersentation (SSR) learning
synthetic aperture radar (SAR) image
target classification
Online Access:https://ieeexplore.ieee.org/document/10269665/

Internet

https://ieeexplore.ieee.org/document/10269665/

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