A Trimodel SAR Semisupervised Recognition Method Based on Attention-Augmented Convolutional Networks

A Trimodel SAR Semisupervised Recognition Method Based on Attention-Augmented Convolutional Networks

Semisupervised learning in synthetic aperture radars (SARs) is one of the research hotspots in the field of radar image automatic target recognition. It can efficiently deal with challenging environments where there are insufficient labeled samples and large unlabeled samples in the SAR dataset. In...

Full description

Bibliographic Details
Main Authors: Sifan Yan, Yaotian Zhang, Fei Gao, Jinping Sun, Amir Hussain, Huiyu Zhou
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Consistency regularization
convolutional networks
self-attention
semisupervised learning (SSL)
synthetic aperture radar (SAR)
Online Access:https://ieeexplore.ieee.org/document/9933710/

Internet

https://ieeexplore.ieee.org/document/9933710/

Similar Items