Modelfest and contrast-interrelation-function data predicted by a retinal model

The automatic implementation of decoders for a visual perception is achieved as follows. The action described by a production rule is realized by means of the decoder in which a pattern of connections coreesponds to that of stimuli. According to "S.Karasawa,(Proc. of CCCT, Vol.5, pp.194-1999, Austin, Texas, August, 2004)", each program mable controllable connection among inputs is realized by a floating gate avalanche injection MOS FET, where inverted signals are used at writing, and the detection of matching between inputs and connections is carried out by using the signal source in which low level signal is provided via comparatively smaller resistance than high level.

Object segregation and local gist vision using low-level geometry

Multi-scale representations of lines, edges and keypoints on the basis of simple, complex and end-stopped cells can be used for object categorisation and recognition (Rodrigues and du Buf, 2009 BioSystems 95 206-226). These representations are complemented by saliency maps of colour, texture, disparity and motion information, which also serve to model extremely fast gist vision in parallel with object segregation. We present a low-level geometry model based on a single type of self-adjusting grouping cell, with a circular array of dendrites connected to edge cells located at several angles.