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- W2072654523 abstract "A computational theory and neural architecture for affine invariant pattern analysis is presented. The orbit of an image pattern under the two dimensional affine transformation group is defined as an invariant pattern class. An analog neural dynamical system with Lie germs is able to compute the distance between the orbit of a given image pattern and a template. Any pattern that is affine reachable to the template (i.e., on the same affine orbit as the template) will have zero distance while others will have larger than zero distances. The key component of this neural system is a type of artificial neuron named Lie germs. Via their receptive fields, these neurons perform the function of the infinitesimal transforms of the affine Lie group on the Gabor representation domain. The responses of the Lie germs generate the vector field of the neural dynamical system tangent to the affine orbits and make the affine orbital motion of the neural dynamical system. A computer simulation of the artificial neural system is also presented." @default.
- W2072654523 created "2016-06-24" @default.
- W2072654523 creator A5058313238 @default.
- W2072654523 date "1995-04-17" @default.
- W2072654523 modified "2023-09-23" @default.
- W2072654523 title "<title>Artificial neural system with Lie germs for affine invariant pattern analysis</title>" @default.
- W2072654523 doi "https://doi.org/10.1117/12.205190" @default.
- W2072654523 hasPublicationYear "1995" @default.
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