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Proceedings Paper

Supersymmetry For Cognitive Science
Author(s): Brian J. Flanagan
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Paper Abstract

Machine vision may be understood as an attempt to replicate natural vision. The latter process is associated with neural networks. Light enters the eye and sets in motion processes which culminate in observed patterns of color. Light is, of course, an electromagnetic phenomenon. Our nerve cells communicate with each other via electrochemical means. To say that a process is electrochemical is to say that it is electromagnetic, involving the exchange of photons among electrons. It seems, therefore, that we ought to be able to understand vision in terms of the physical theory of electromagnetism. Historically, however, it has been held that such properties as color do not belong to the physical world. Color has long been considered to be a mental effect of physical stimuli. Nevertheless, it is generally understood that color is related to the energy, wavelength, and frequency of the photons which give rise to the "mental" impression of hue and intensity and so forth. Similar arguments and propositions can be made for all of the sensory modalities, but we will restrict our attention to vision for the time being. If, with Mach, we accept that colors are physical objects, we are obliged to seek a suitable place for them within the body of physical theory. Where should we locate them? Colors are given to us as simple entities, having no parts: We can point to an object that is blue, but we cannot say what blue is. Color is given to us as elemental. In a formal theory, we have a number of elements, rules for joining them, well-formed formulae, and methods of proof. It seems to make good sense to place color among the elements of a formal theory (T). If our mind/brains can be modelled by a formal theory, it follows logically that we should not be able to define our elements - i.e., if we could define our elements, they would not be elements.

Paper Details

Date Published: 27 March 1989
PDF: 5 pages
Proc. SPIE 1002, Intelligent Robots and Computer Vision VII, (27 March 1989); doi: 10.1117/12.960287
Show Author Affiliations
Brian J. Flanagan

Published in SPIE Proceedings Vol. 1002:
Intelligent Robots and Computer Vision VII
David P. Casasent, Editor(s)

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