DocumentCode
1908446
Title
An ARTMAP based hybrid neural network for shift invariant Chinese character recognition
Author
Hung, Cheng-An ; Lin, Sheng-Fuu
Author_Institution
Dept. of Control Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan
fYear
1993
fDate
1993
Firstpage
1600
Abstract
An ARTMAP-based hybrid neural network is proposed to recognize position-shifted Chinese characters. The faster learning speed of a hybrid architectures makes practical the use of neural networks in large-scale neural computation. Four translation-invariant transformations are used to extract features of two-dimensional patterns. The results of experimentation with three different hybrid neural networks are presented
Keywords
character recognition; feature extraction; learning (artificial intelligence); neural nets; ARTMAP; Chinese character recognition; feature extraction; hybrid architectures; hybrid neural network; learning; translation-invariant transformations; Character recognition; Computer architecture; Computer networks; Control engineering; Feature extraction; Gain control; Large-scale systems; Neural networks; Resonance; Subspace constraints;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1993., IEEE International Conference on
Conference_Location
San Francisco, CA
Print_ISBN
0-7803-0999-5
Type
conf
DOI
10.1109/ICNN.1993.298795
Filename
298795
Link To Document