Abstract
Humans can recognize familiar, but unexpected objects, belonging to highly variable object classes, in a fraction of a second — a few hundred cycles of the neural visual "hardware". This position paper suggests computational techniques that could serve as a basis for this type of object recognition if implemented on appropriate parallel hardware.

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