Cellular neural networks and visual computing: foundations and applications
Cellular neural networks and visual computing: foundations and applications
Vision: A Computational Investigation into the Human Representation and Processing of Visual Information
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The Spotlight Models of attention that rely upon a bottom-up approach specifically through the dorsal pathways, can be modeled using multi-scale Gaussian pyramids with excitatory-inhibitory feedforward cellular neural networks (CNN) as feature detectors. Here we propose a modified disinhibitory zero-feedback CNN model derived out of a linear combination of three Gaussians only, that explains many brightness perception based psychophysical phenomena unexplainable with the old model and in the process predicts three different input cloning templates for global smoothing, global enhancement, as well as controlled smoothing and enhancement of retinal images within the focus of attention. The proposed approach provides new clues, based on the psychophysical stimuli, suggestive of a role of top-down attentional control possibly through the ventral pathways, even at the stage of low-level vision.