Share Email Print
cover

Proceedings Paper

Dependence of ATR system performance on size of training sets
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Automatic target recognition systems often have parameters that are estimated using training data. These parameters are then used in an implementation of the system as if they are the true parameters. The training sets consist of independent and identically distributed copies of the data given the target type. In an ideal case, we analyze the degradation in performance of such systems as a function of the size of the training sets. The training sets consist of independent and identically distributed copies of the data given the target type. The ideal performance is determined by the true parameters and is characterized in terms of a receiver operating characteristic (ROC) for a two-target problem. For a finite-sized training set the ROC curves fall below the ideal and converge to the ideal as the size of the training sets grows. Since in practical systems we have only a very limited amount of training data, it is desirable to quantify the degradation based on the size of the training sets. This will allow a prediction of the difference between performance obtained empirically and the optimal performance. Laplace approximations for the performance are explored. We study a Gaussian model in detail.

Paper Details

Date Published: 13 August 1999
PDF: 10 pages
Proc. SPIE 3721, Algorithms for Synthetic Aperture Radar Imagery VI, (13 August 1999); doi: 10.1117/12.357688
Show Author Affiliations
Joseph A. O'Sullivan, Washington Univ. (United States)
Natalia A. Schmid, Washington Univ. (United States)


Published in SPIE Proceedings Vol. 3721:
Algorithms for Synthetic Aperture Radar Imagery VI
Edmund G. Zelnio, Editor(s)

© SPIE. Terms of Use
Back to Top