Cortical dynamics of three-dimensional form, color, and brightness perception I: Monocular theory
Neural networks and natural intelligence
Cortical dynamics of three-dimensional form, color, and brightness perception II: Binocular theory
Neural networks and natural intelligence
A VLSI neural network for color constancy
NIPS-3 Proceedings of the 1990 conference on Advances in neural information processing systems 3
Neural mechanisms for representing surface and contour features
Emergent neural computational architectures based on neuroscience
Neural Mechanisms for Representing Surface and Contour Features
Emergent Neural Computational Architectures Based on Neuroscience - Towards Neuroscience-Inspired Computing
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The filling-in theory of brightness perception has gained much attention recently owing to the success of vision models. However, the theory and its instantiations have suffered from incorrectly dealing with transitive brightness relations. This paper describes an advance in the filling-in theory that overcomes the problem. The advance is incorporated into the BCS/FCS neural network model, which allows it, for the first time, to account for all of Arend's test stimuli for assessing brightness perception models. The theory also suggests a new teleology for parallel ON-and OFF-channels.