Precision of a radial basis function neural network tracking method

被引：2
|
作者：
Hanan, J [1 ]
Zhou, HY [1 ]
Chao, TH [1 ]
机构：
[1] Jet Prop Lab, Pasadena, CA 91109 USA
来源：
OPTICAL PATTERN RECOGNITION XIV | 2003年 / 5106卷
关键词：
autonomous tracking; neural network; target recognition; data reduction;
D O I：
10.1117/12.501406
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The precision of a radial basis function (RBF) neural network based tracking method has been assessed against real targets. Intensity profile feature extraction was used to build a model in real time, evolving with the target. Precision was assessed against traditionally measured frame-by-frame measurements from the recorded data set. The results show the potential limit for the technique and reveal intricacies associated with empirical data not necessarily observed in simulations.
引用
收藏
页码：146 / 153
页数：8
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