Synthetic aperture radar target recognition of incomplete training datasets via Siamese network

Synthetic aperture radar target recognition of incomplete training datasets via Siamese network

Synthetic aperture radar (SAR) target recognition can provide effective target category information and becomes the key part of SAR image application. Machine learning and deep learning are two main methods of target recognition. Normally, through the massive image features learning, the trained mod...

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Bibliographic Details
Main Authors: Jiaxin Tang, Fan Zhang, Qiang Yin, Wei Hu
Format: Article
Language:English
Published: Wiley 2019-09-01
Series:The Journal of Engineering
Subjects:
image classification
learning (artificial intelligence)
radar target recognition
synthetic aperture radar
radar imaging
radar computing
convolutional neural nets
feature extraction
synthetic aperture radar target recognition
incomplete training datasets
effective target category information
sar image application
machine learning
deep learning
massive image features
target images
data samples
dual-input siamese convolution neural network
sar target recognition
training method
data enhancement method
samples classification
testing data
Online Access:https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0566

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https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0566

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