Paper
4 May 2018 Application and performance of convolutional neural networks to SAR
Author Affiliations +
Abstract
Implementation of convolutional neural networks (CNNs) as classifiers has only recently found application in SAR multi-target classification. Despite the creation of several successful architectures, a general approach to CNN design and training has not been determined. In this paper, the basics of CNN architecture and learning algorithms are discussed. The MSTAR data set is used to demonstrate the effect of individual parameter changes to overall network performance.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Maxine R. Fox and Ram M. Narayanan "Application and performance of convolutional neural networks to SAR", Proc. SPIE 10633, Radar Sensor Technology XXII, 1063304 (4 May 2018); https://doi.org/10.1117/12.2305852
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Cited by 1 scholarly publication.
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KEYWORDS
Convolutional neural networks

Network architectures

Synthetic aperture radar

Neural networks

Neurons

Feature extraction

Convolution

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