Self-organization and associative memory: 3rd edition
Self-organization and associative memory: 3rd edition
Invariant Image Recognition by Zernike Moments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
An Adaptive Contour Closure Algorithm and Its Experimental Evaluation
IEEE Transactions on Pattern Analysis and Machine Intelligence
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We give a methodology for the evaluation and comparison of object recognition systems. The methodology is based on indicators of two kinds: (1) statistical and (2) algorithmic. Statistical indicators measure the significance of the performance difference between different systems and rank the performances when the difference is significant. Of the various statistical indicators, we use the Kruskal-Wallis H test. Algorithmic indicators include the usual space and time complexity measures, and various performance curves in variables of error and test data sample size. We illustrate the methodology to evaluate a number of pattern classifiers.