Efficiency in the Generation of Hierarchical Feature Detectors in Neural Nets

Oleg G. Jakubowicz

doi:10.1117/12.969996

1 March 1990 Efficiency in the Generation of Hierarchical Feature Detectors in Neural Nets

Oleg G. Jakubowicz

Proceedings Volume 1198, Sensor Fusion II: Human and Machine Strategies; (1990) https://doi.org/10.1117/12.969996
Event: 1989 Symposium on Visual Communications, Image Processing, and Intelligent Robotics Systems, 1989, Philadelphia, PA, United States

Abstract

Biologically in the primary visual area in the brain there is a full set of elementary feature detectors at every location in the retinal field. These detectors are akin to the two dimensional edge and bar detectors commonly used in computer vision. We present in this paper biological simulation details of how these particular detectors most probably might be neurobiologically constructed and organized into a topologically ordered output plane. Then we point out the pitfall of over-representation of information that can occur in naive self-organizing neural network models for vision and present. how our properly constructed network overcomes this problem. This paper is intended to give some productive guidelines for constructing self-organizing networks whose cells have locally receptive fields.

Citation Download Citation

Oleg G. Jakubowicz "Efficiency in the Generation of Hierarchical Feature Detectors in Neural Nets", Proc. SPIE 1198, Sensor Fusion II: Human and Machine Strategies, (1 March 1990); https://doi.org/10.1117/12.969996

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