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Proceedings Paper

Precision of a radial basis function neural network tracking method
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Paper Abstract

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.

Paper Details

Date Published: 6 August 2003
PDF: 8 pages
Proc. SPIE 5106, Optical Pattern Recognition XIV, (6 August 2003); doi: 10.1117/12.501406
Show Author Affiliations
Jay Hanan, Jet Propulsion Lab. (United States)
Hanying Zhou, Jet Propulsion Lab. (United States)
Tien-Hsin Chao, Jet Propulsion Lab. (United States)


Published in SPIE Proceedings Vol. 5106:
Optical Pattern Recognition XIV
David P. Casasent; Tien-Hsin Chao, Editor(s)

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