The visual system is probably the most important sensory modality for humans as well as for mammals. Its first and best-known part is the retina, which is not a mere photoreceptor or static camera but a sophisticated feature preprocessor with a continuous input and several parallel output channels . These channels build up a "visual language" and any realistic mammalian retina model should generate the elements of this visual language. The framework of mammalian retinal modeling via multi-layer CNN has been recently published . In the present paper we show the transformation of this model into a CNN-UM algorithm and the design steps of the implementation of this complex visual language. The analogic algorithm consists of a series of different complex-cell CNN dynamics . The algorithm is feasible on a recently fabricated complex cell CNN-UM chip. The decomposition method of the multilayer mammalian retina model will be discussed in detail.
|Journal||Proceedings - IEEE International Symposium on Circuits and Systems|
|Publication status||Published - Jan 1 2002|
|Event||2002 IEEE International Symposium on Circuits and Systems - Phoenix, AZ, United States|
Duration: May 26 2002 → May 29 2002
ASJC Scopus subject areas
- Electrical and Electronic Engineering