Learning Shape Descriptions

نویسندگان

  • Jonathan H. Connell
  • Michael Brady
چکیده

We report on initial experiments with an implemented learning system whose inputs are images of two-dimensional shapes. The system first builds semantic network shape descriptions based on Brady's smoothed local symmetry representation. It learns shape models from them using a modified version of Winston's ANALOGY program. The learning program uses only positive examples, and is capable of learning disjunctive concepts. We discuss the lcarnability of shape descriptions.

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تاریخ انتشار 1985