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註釋Abstract: "Intelligent systems are faced with the problem of securing a principled relationship between the world and its internal representation. I propose a unified approach to visual representation, based on Shepard's (1968) notion of second-order isomorphism. According to the proposed theory, a shape is represented by its similarity to a number of reference shapes, measured in a high-dimensional space of elementary features. The result is a philosophically appealing, computationally feasible and formally veridical representation of a distal shape space, which addresses the needs of shape categorization and can be used to derive a range of models of perceived similarity."