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Journal of Electronic Imaging

Misrepresentations of signal detection theory and a model-free approach to human image classification
Author(s): Jerry D. Balakrishnan; Justin A. MacDonald
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Paper Abstract

Experimental methods and statistics derived from signal detection theory are frequently used to compare two imaging techniques, to predict human performance under different parameterizations of an imaging system, and to distinguish variables related to human visual perception from variables related to decision making. We review recent experimental results suggesting that the assumptions of signal detection theory are fundamentally unsound. Instead of shifting decision criteria under different priors, humans appear to alter the information assimilation process, representing images from categories with high prior probability more accurately (less variance) than images from categories with low prior probability. If this hypothesis is correct, detection theory measures such as d8 and area under the receiver operating characteristic may be misleading or incomplete. We propose an alternative approach that can be used to quantify the effects of suboptimal decision making strategies without relying on a model of detection structure.

Paper Details

Date Published: 1 April 2001
PDF: 9 pages
J. Electron. Imag. 10(2) doi: 10.1117/1.1344188
Published in: Journal of Electronic Imaging Volume 10, Issue 2
Show Author Affiliations
Jerry D. Balakrishnan, Purdue Univ. (United States)
Justin A. MacDonald, Purdue Univ. (United States)

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