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Proceedings Paper

Using predictive distributions to estimate uncertainty in classifying landmine targets
Author(s): Ryan Close; Ken Watford; Taylor Glenn; Paul Gader; Joseph Wilson
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Paper Abstract

Typical classification models used for detection of buried landmines estimate a singular discriminative output. This classification is based on a model or technique trained with a given set of training data available during system development. Regardless of how well the technique performs when classifying objects that are 'similar' to the training set, most models produce undesirable (and many times unpredictable) responses when presented with object classes different from the training data. This can cause mines or other explosive objects to be misclassified as clutter, or false alarms. Bayesian regression and classification models produce distributions as output, called the predictive distribution. This paper will discuss predictive distributions and their application to characterizing uncertainty in the classification decision, from the context of landmine detection. Specifically, experiments comparing the predictive variance produced by relevance vector machines and Gaussian processes will be described. We demonstrate that predictive variance can be used to determine the uncertainty of the model in classifying an object (i.e., the classifier will know when it's unable to reliably classify an object). The experimental results suggest that degenerate covariance models (such as the relevance vector machine) are not reliable in estimating the predictive variance. This necessitates the use of the Gaussian Process in creating the predictive distribution.

Paper Details

Date Published: 23 May 2011
PDF: 8 pages
Proc. SPIE 8017, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XVI, 801724 (23 May 2011); doi: 10.1117/12.887357
Show Author Affiliations
Ryan Close, Univ. of Florida (United States)
Ken Watford, Univ. of Florida (United States)
Taylor Glenn, Univ. of Florida (United States)
Paul Gader, Univ. of Florida (United States)
Joseph Wilson, Univ. of Florida (United States)

Published in SPIE Proceedings Vol. 8017:
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XVI
Russell S. Harmon; John H. Holloway Jr.; J. Thomas Broach, Editor(s)

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