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Summary: A Selective Attention Based Method for Visual Pattern Recognition
Albert Ali Salah (SALAH@Boun.Edu.Tr)
Ethem Alpaydin (ALPAYDIN@Boun.Edu.Tr)
Lale Akarun (AKARUN@Boun.Edu.Tr)
Department of Computer Engineering; Bogazic¸i University,
80815 Bebek Istanbul, Turkey
Abstract
Parallel pattern recognition requires great computational
resources. It is desirable from an engineering point of
view to achieve good performance with limited resources.
For this purpose, we develop a serial model for visual pat-
tern recognition based on the primate selective attention
mechanism. The idea in selective attention is that not all
parts of an image give us information. If we can attend to
only the relevant parts, we can recognize the image more
quickly and using less resources. We simulate the primi-
tive, bottom-up attentive level of the human visual system
with a saliency scheme, and the more complex, top-down,
temporally sequential associative level with observable
Markov models. In between, there is an artificial neu-
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