Abstract
This paper analyzes properties of a certain class of approximation techniques -- HyperBF networks -- in face perception tasks. The problem of gender classification and identification is addressed using a geometrical description of faces, extracted automatically from digitized pictures of frontal views of people without facial hair. The HyperBF networks perform satisfactorily on the classification tasks and exhibit the phenomenon of caricaturing, previously reported in psychophysical experiments.
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