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Emergence of ontological relations from visual data with self-organizing maps AbstractIn this paper we examine how Self-Organizing Maps (SOMs) can be used in detecting and describing emergent ontological relations between semantic objects and object classes in a visual database. The ontological relations we have studied include co-existence, taxonomies of visual and semantic similarity and spatial relationships. The used database contains 2618 images each of which belongs to one or more of ten predefined semantic classes.
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