<> "The repository administrator has not yet configured an RDF license."^^ . <> . . "Neural networks as a model for visual perception: what is lacking?"^^ . "A central mystery of visual perception is the classical problem of invariant object recognition: Different appearances of an object can be perceived as ``the same'', despite, e.g., changes in position or illumination, distortions, or partial occlusion by other objects. This article reports on a recent email discussion over the question whether a neural network can learn the simplest of these invariances, i.e. generalize over the position of a pattern on the input layer, including the author's view on what ``learning shift-invariance'' could mean. That definition leaves the problem unsolved. A similar problem is the one of learning to detect symmetries present in an input pattern. It has been solved by a standard neural network requiring some 70000 input examples. Both leave some doubt if backpropagation learning is a realistic model for perceptual processes. Abandoning the view that a stimulus-response system showing the desired behavior must be learned from scratch, yields a radically different solution. Perception can be seen as an active process that rapidly converges from some initial state to an ordered state, which in itself codes for a percept. As an example, I will present a solution to the visual correspondence problem, which greatly alleviates both problems mentioned above."^^ . "1998" . . . . . . . "Rolf P."^^ . "Würtz"^^ . "Rolf P. Würtz"^^ . . . . . . "Neural networks as a model for visual perception: what is lacking? (Postscript)"^^ . . . . . . "rolf-cogsys98.ps"^^ . . "HTML Summary of #507 \n\nNeural networks as a model for visual perception: what is lacking?\n\n" . "text/html" . . . "Animal Cognition" . . . "Cognitive Psychology" . . . "Complexity Theory" . . . "Machine Vision" . . . "Neural Nets" . . . "Neural Modelling" . .