Hierarchical Fusion of Convolutional Neural Networks and Attributed Scattering Centers with Application to Robust SAR ATR

Hierarchical Fusion of Convolutional Neural Networks and Attributed Scattering Centers with Application to Robust SAR ATR

This paper proposes a synthetic aperture radar (SAR) automatic target recognition (ATR) method via hierarchical fusion of two classification schemes, i.e., convolutional neural networks (CNN) and attributed scattering center (ASC) matching. CNN can work with notably high effectiveness under the stan...

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Bibliographic Details
Main Authors: Chuanjin Jiang, Yuan Zhou
Format: Article
Language:English
Published: MDPI AG 2018-05-01
Series:Remote Sensing
Subjects:
synthetic aperture radar (SAR)
automatic target recognition (ATR)
hierarchical fusion
convolutional neural networks (CNN)
attributed scattering center (ASC)
Online Access:http://www.mdpi.com/2072-4292/10/6/819

Internet

http://www.mdpi.com/2072-4292/10/6/819

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