SA<inline-formula><tex-math notation="LaTeX">$^{2}$</tex-math></inline-formula>Net: Ship Augmented Attention Network for Ship Recognition in SAR Images

SA<inline-formula><tex-math notation="LaTeX">$^{2}$</tex-math></inline-formula>Net: Ship Augmented Attention Network for Ship Recognition in SAR Images

Maritime surveillance is extensively concerned by worldwide authorities, in which ship recognition in synthetic aperture radar (SAR) images is a significant and fundamental component. Though some development has been achieved in the SAR ship recognition task, two areas remain inadequately explored,...

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Bibliographic Details
Main Authors: Yuanzhe Shang, Wei Pu, Danling Liao, Ji Yang, Congwen Wu, Yulin Huang, Yin Zhang, Junjie Wu, Jianyu Yang, Jianqi Wu
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Synthetic aperture radar (SAR)
ship recognition
convolutional neural networks (CNNs)
shape priory knowledge
feature augmented module
scale attention module (SAM)
Online Access:https://ieeexplore.ieee.org/document/10256050/

Internet

https://ieeexplore.ieee.org/document/10256050/

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