Abstract
We constructed a universal system for object recognition, which uses preliminary training based on sample images of “objects” and “non-objects.” The images are represented by separate points in multi-dimensional space of features. A recognition system which uses the features space obtained on the basis of lateral-inhibition type functions is described.
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