GEOMETRIC MOMENT INVARIANCE IN CHARACTER-RECOGNITION USING ARTIFICIAL NEURAL NETWORKS (ANN)

被引:0
作者
SANOSSIAN, HYY
EVANS, DJ
机构
[1] Parallel Algorithms Research Centre, University of Technology, Loughborough, Leics
关键词
ANN; BACKPROPAGATION; GRADIENT RANGE BASED HEURISTIC; LEARNING RATES;
D O I
10.1080/00207169408804347
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
A number of researchers have used ANNs with different techniques to recognize invariant patterns (Lee and Oldham (1990), Burr (1988), Khotanzad and Lu (1990), Barnard and Casasent (1991), Widrow, Winter and Baxter (1987)). These techniques can be broadly classified as preprocessing the input signal to be invariant to geometrical differences. In this paper the back propagation (BP) and Gradient Range Based Heuristic (GRBH) algorithms for ANN training are presented and their learning rates compared.
引用
收藏
页码:143 / 153
页数:11
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