Abstract
In this paper, cellular neural networks (CNNs) for hexagonal image processing (HIP) frameworks has been proposed. In this paper, we combine two distinguished researches; one is CNNs, which provide efficient computing abilities. The other is HIP, which contains most compact structure. Both CNNs and HIP are inspired by biology. CNNs present the behaviors which are most similar to the retina of human's eyes, and HIP presents architecture which is also most similar to the distribution of cells on the retina.
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