1 April 2001 Misrepresentations of signal detection theory and a model-free approach to human image classification
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J. of Electronic Imaging, 10(2), (2001). doi:10.1117/1.1344188
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.
Jerry D. Balakrishnan, Justin A. MacDonald, "Misrepresentations of signal detection theory and a model-free approach to human image classification," Journal of Electronic Imaging 10(2), (1 April 2001). http://dx.doi.org/10.1117/1.1344188
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KEYWORDS
Detection theory

Image processing

Signal detection

Data modeling

Image classification

Signal processing

Visualization

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