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Center for Nonlinear Studies |
Enabling computers to understand images remains one of the hardest open problems in artificial intelligence. No machine vision system comes close to matching human ability at identifying the contents of images or visual scenes or at recognizing similarity between different scenes, even though such abilities pervade human cognition. In this talk I will describe research---currently in early stages---on bridging the gap between low-level perception and higher-level image understanding by integrating a cognitive model of perceptual organization and analogy-making with a neural model of the visual cortex.
Host: Garrett Kenyon, P-21