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We describe a Bayesian network implementation of a theory of concepts that is motivated by observations from the philosophical debate between Lexical Concept Empiricism and Lexical Concept Nativism. According to our theory, Baptizing Meanings for Concepts (BMC), concepts are acquired by hypothesizing latent kinds/categories to explain observed co-occurrences of sets of properties in a group of objects...
In this presentation for the panel at MCAM07, I put forward the transition of modeling the world as was done on a large scale in computer vision before the year 2000, to the current situation where there have been considerable successes with multimedia analysis by learning from the world. We make a plead for the last type of learned features, modeling only the scene accidental conditions and learning...
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