CURSIVE WORD RECOGNITION BASED ON INTERACTIVE ACTIVATION AND EARLY VISUAL PROCESSING MODELS

被引：5

作者：

Ruiz-Pinales, Jose ^{[1
]}

Jaime-Rivas, Rene ^{[1
]}

Lecolinet, Eric ^{[2
]}

Castro-Bleda, Maria Jose ^{[3
]}

机构：

[1] Univ Guanajuato, Salamanca, Gto, Mexico

[2] Ecole Natl Super Telecommun Bretagne, INFRES, Paris, France

[3] Univ Politecn Valencia, E-46071 Valencia, Spain

来源：

INTERNATIONAL JOURNAL OF NEURAL SYSTEMS | 2008年 / 18卷 / 05期

关键词：

Handwriting recognition; interactive activation model; feedforward model; convolutional neural networks; reading models;

D O I：

10.1142/S0129065708001683

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We present an off-line cursive word recognition system based completely on neural networks: reading models and models of early visual processing. The first stage (normalization) preprocesses the input image in order to reduce letter position uncertainty; the second stage (feature extraction) is based on the feedforward model of orientation selectivity; the third stage (letter pre-recognition) is based on a convolutional neural network, and the last stage (word recognition) is based on the interactive activation model.

引用

页码：419 / 431

页数：13

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