EℓI-chan for Intermediate Features

Publication Type

Conference Proceeding Article

Publication Date

10-1993

Abstract

We propose an EℓI-chan, Emergent ℓocal Indicator Mechanism, to model the representation and self-organization of intermediate features in the visual pathway. This model is motivated by the orientation specificity in the primary visual cortex. Our simulations of EℓI-chan demonstrate that local indicators of the locations of intermediate features emerge, and they become the seeds for unsupervised learning and pattern recognition; EℓI-chan predicts those portions of the input imagery where intermediate features potentially exist. Hence, EℓI-chan can be used to define a set of intermediate features for adaptation, and the onwards processing in a hierarchical pattern recognition system.

Discipline

Physical Sciences and Mathematics

Research Areas

Strategy and Organisation

Publication

IJCNN '93 Nagoya: Proceedings of the International Joint Conference on Neural Networks, 25-29 October 1993, Japan

First Page

2508

Last Page

2511

ISBN

9780780314214

Identifier

10.1109/IJCNN.1993.714234

Publisher

IEEE

City or Country

Piscataway, NJ

Additional URL

https://doi.org/10.1109/IJCNN.1993.714234

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