GPU-enabled high performance feature modeling for ATR applications
Dept. of Comput. Sci., Louisiana Tech Univ., Ruston, LA, USA
Proceedings of the IEEE 2010 National Aerospace and Electronics Conference (NAECON), 2010
@inproceedings{dessauer2010gpu,
title={GPU-enabled high performance feature modeling for ATR applications},
author={Dessauer, M.P. and Hitchens, J. and Dua, S.},
booktitle={Aerospace and Electronics Conference (NAECON), Proceedings of the IEEE 2010 National},
pages={92–98},
organization={IEEE},
year={2010}
}
Computational methods for automatic target recognition are constrained by the need to analyze increasingly high-dimensional sensor data in real time. Parallel processing has the potential to speed up computational bottlenecks in many automatic target recognition (ATR) methods. We will implement parallelized versions of target tracking methods and discuss gains in algorithm completion time.
May 27, 2011 by hgpu
