GPU-enabled High Performance Feature Modeling for ATR Applications

被引：2
|
作者：
Dessauer, Michael P. [1 ]
Hitchens, Joshua [1 ]
Dua, Sumeet [1 ]
机构：
[1] Louisiana Tech Univ, Dept Comp Sci, Ruston, LA 71270 USA
来源：
PROCEEDINGS OF THE IEEE 2010 NATIONAL AEROSPACE AND ELECTRONICS CONFERENCE (NAECON) | 2010年
关键词：
machine vision; object recognition; parallel processing; tracking);
D O I：
10.1109/NAECON.2010.5712930
中图分类号：
V [航空、航天];
学科分类号：
08 ; 0825 ;
摘要：
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.
引用
收藏
页码：92 / 98
页数：7
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