Cascade fuzzy ART: a new extensible database for model-based object recognition

Hai-Lung Hung; Hong-Yuan Mark Liao; Shing-Jong Lin; Wei-Chung Lin; Kuo-Chin Fan

doi:10.1117/12.233231

27 February 1996 Cascade fuzzy ART: a new extensible database for model-based object recognition

Hai-Lung Hung, Hong-Yuan Mark Liao, Shing-Jong Lin, Wei-Chung Lin, Kuo-Chin Fan

Proceedings Volume 2727, Visual Communications and Image Processing '96; (1996) https://doi.org/10.1117/12.233231
Event: Visual Communications and Image Processing '96, 1996, Orlando, FL, United States

Abstract

In this paper, we propose a cascade fuzzy ART (CFART) neural network which can be used as an extensible database in a model-based object recognition system. The proposed CFART networks can accept both binary and continuous inputs. Besides, it preserves the prominent characteristics of a fuzzy ART network and extends the fuzzy ART's capability toward a hierarchical class representation of input patterns. The learning processes of the proposed network are unsupervised and self-organizing, which include coupled top-down searching and bottom-up learning processes. In addition, a global searching tree is built to speed up the learning and recognition processes.

Citation Download Citation

Hai-Lung Hung, Hong-Yuan Mark Liao, Shing-Jong Lin, Wei-Chung Lin, and Kuo-Chin Fan "Cascade fuzzy ART: a new extensible database for model-based object recognition", Proc. SPIE 2727, Visual Communications and Image Processing '96, (27 February 1996); https://doi.org/10.1117/12.233231

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