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...

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Detalhes bibliográficos

Principais autores:	Sifan Yan, Yaotian Zhang, Fei Gao, Jinping Sun, Amir Hussain, Huiyu Zhou
Formato:	Artigo
Idioma:	Inglês
Publicado em:	IEEE 2022-01-01
coleção:	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Assuntos:	Consistency regularization convolutional networks self-attention semisupervised learning (SSL) synthetic aperture radar (SAR)
Acesso em linha:	https://ieeexplore.ieee.org/document/9933710/
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