Autonomic Face Recognition Using the NoN Approach

Abstract

The NoN model is based on locally parallel and globally coordinated transformations in which the neurons or computational units form distributed networks, which themselves link to form larger networks. This models the structures in the cerebral cortex described by Mountcastle and the architecture based on that proposed for information processing by Sutton. In the proposed implementation, face images are processed by a nested family of locally operating networks along with a hierarchically superior network that classifies the information from each of the local networks. The results of the experiments yielded a maximum of 98.5% recognition accuracy and an average of 97.4% recognition accuracy on a benchmark database. The NoN model may be viewed as one in a hierarchy that leads eventually to quantum models.

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Cite this paper

@inproceedings{Scott2006AutonomicFR, title={Autonomic Face Recognition Using the NoN Approach}, author={Willie L. Scott}, year={2006} }