Hong-Yuan Mark Liao, Hai-Lung Hung, Chwen-Jye Sze Shing-Jong Lin,...  Home/Search
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Abstract: In this report, we propose a cascade fuzzy adaptive Hamming net (CFAHN) which can function as an extensible database in a model-based object recognition system. The proposed CFAHN can accept both binary and analog inputs. The architecture of a CFAHN not only preserves the prominent characteristics of the FAHN (i.e., parallel pattern matching, fast learning and stable categorization), but also extends its capability to the hierarchical class representation of input patterns. The developed CFAHN... (Update)
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BibTeX entry: (Update)
@misc{ liao-cascade,
author = "Hong-Yuan Mark Liao",
title = "Cascade Fuzzy Adaptive Hamming Net: A Coarse-to-Fine Representation Scheme
for Object Recognition",
url = "citeseer.ist.psu.edu/221993.html" }
Citations (may not include all citations):700 Self-Organization and Associative Memory (context) - Kohonen - 1989
188 A Massively Parallel Architecture for a SelfOrganizing Neura.. (context) - Carpenter, Grossberg - 1987
81 Adaptive Pattern Recognition and Neural Networks (context) - Pao - 1989 ACM
80 Fuzzy ART: Fast Stable Learning and Categorization of Analog.. (context) - Carpenter, Grossberg et al. - 1991 ACM
25 ART 3: Hierarchical Search Using Chemical Transmitters in Se.. (context) - Carpenter, Grossberg - 1990
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7 An ART-based Modular Architecture for Learning Hierarchical .. - Bartfai - 1995 DBLP
5 Adaptive Hamming Net: A Fast-Learning ART 1 Model Without Se.. (context) - Hung, Lin - 1995
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