@inproceedings{165fae1c0bba4c528efea289c2a7b27e,
title = "Application and performance of convolutional neural networks to SAR",
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.",
author = "Fox, {Maxine R.} and Narayanan, {Ram M.}",
note = "Funding Information: This work was supported by the U.S. Office of Naval Research under Grant # N00014-16-1-2354 kindly provided by Dr. Joong Kim. Publisher Copyright: {\textcopyright} 2018 SPIE.; Radar Sensor Technology XXII 2018 ; Conference date: 16-04-2018 Through 18-04-2018",
year = "2018",
doi = "10.1117/12.2305852",
language = "English (US)",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Armin Doerry and Ranney, {Kenneth I.}",
booktitle = "Radar Sensor Technology XXII",
address = "United States",
}