Cumincad : CUMINCAD Papers : Paper 2790:A Symbolic/Neural Hybrid Approach to Emergent Subshape Recognition

authors	Mon Chu
year	1996
title	A Symbolic/Neural Hybrid Approach to Emergent Subshape Recognition
doi	https://doi.org/10.52842/conf.caadria.1996.191
source	CAADRIA ‘96 [Proceedings of The First Conference on Computer Aided Architectural Design Research in Asia / ISBN 9627-75-703-9] Hong Kong (Hong Kong) 25-27 April 1996, pp. 191-198
summary	Recognizing emergent subshape is one kind of human visual behaviour. People usually recognize several distinct emergent subshapes from primary shapes and give them different interpretations. This paper presents a symbolic/connectionist hybrid system to provide computers the ability of this kind. Through this approach, the recognition system is divided into three modules. Source images are sent to the first module, that is a connectionist network, of the hybrid system. The network is responsible for transforming the source image into abstract visual data, named Pre-attention Distribution and Local Feature Information. Then, the abstract visual data are processed in the second module that is a symbolic subsystem. The subsystem is responsible for making decision in the Visual Search Attention processes and for managing the features of the whole shape. Finally, another connectionist network takes the previous results from the symbolic subsystem and performs the final recognition.
series	CAADRIA
full text	file.pdf (413,857 bytes)
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