Paper
1 July 1992 Neural network modeling of visual recognition
Rafik Braham
Author Affiliations +
Abstract
The recognition of visual patterns is one of the main application areas of neural networks. Several models have been designed based on the current understanding of visual information processing in the brains of cats and monkeys. Examples of such models are described in the works of Fukushima, Grossberg, von der Malsburg, and others. But because the visual system is very complex and visual information processing consists of several stages, the technical models attempt to reproduce one or a few aspects. The author has been mostly interested in modeling some of the anatomical features of visual areas and understanding their functional significance. In this paper, principles used in popular models are analyzed. Then the structure and design rationale of a vision model is described. In this description, the principles of the model rather than its implementation details are underscored.
© (1992) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Rafik Braham "Neural network modeling of visual recognition", Proc. SPIE 1710, Science of Artificial Neural Networks, (1 July 1992); https://doi.org/10.1117/12.140086
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KEYWORDS
Visual process modeling

Visualization

Information visualization

Neural networks

Visual system

Artificial neural networks

Motion models

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