KECANet: A novel convolutional kernel network for ocean SAR scene classification with limited labeled data

KECANet: A novel convolutional kernel network for ocean SAR scene classification with limited labeled data

The ability of synthetic aperture radar (SAR) to capture maritime phenomena is widely acknowledged. However, ocean SAR scene automatic classification remains challenging due to speckle noise interference, the nonlinearities and poor distinguishability of different geophysical phenomena. Kernel entro...

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Bibliographic Details
Main Authors: Ming Ma, Chengzu Bai, Shuo Zhang, Longxia Qian, Hengqian Yan
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-09-01
Series:Frontiers in Marine Science
Subjects:
synthetic aperture radar
kernel entropy component analysis
convolutional kernel network
oceanic phenomena detection
cholesky decomposition
Online Access:https://www.frontiersin.org/articles/10.3389/fmars.2022.935600/full

Internet

https://www.frontiersin.org/articles/10.3389/fmars.2022.935600/full

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