Digit and command interpretation for electronic book using neural network and genetic algorithm

H. K. Lam; Hung Fat Frank Leung

doi:10.1109/TSMCB.2004.834432

Digit and command interpretation for electronic book using neural network and genetic algorithm

H. K. Lam
, Hung Fat Frank Leung

The Hong Kong Polytechnic University

Research output: Journal article publication › Journal article › Academic research › peer-review

12 Citations (Scopus)

Abstract

This paper presents the interpretation of digits and commands using a modified neural network and the genetic algorithm. The modified neural network exhibits a node-to-node relationship which enhances its learning and generalization abilities. A digit-and-command interpreter constructed by the modified neural networks is proposed to recognize handwritten digits and commands. A genetic algorithm is employed to train the parameters of the modified neural networks of the digit-and-command interpreter. The proposed digit-and-command interpreter is successfully realized in an electronic book. Simulation and experimental results will be presented to show the applicability and merits of the proposed approach.

Original language	English
Pages (from-to)	2273-2283
Number of pages	11
Journal	IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Volume	34
Issue number	6
DOIs	https://doi.org/10.1109/TSMCB.2004.834432
Publication status	Published - 1 Dec 2004

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Digit and command interpretation
Electronic book
Genetic algorithm
Neural networks

ASJC Scopus subject areas

Control and Systems Engineering
Software
General Medicine
Information Systems
Human-Computer Interaction
Computer Science Applications
Electrical and Electronic Engineering

More information

10.1109/TSMCB.2004.834432

http://hdl.handle.net/10397/1420

Cite this

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AU - Leung, Hung Fat Frank

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AB - This paper presents the interpretation of digits and commands using a modified neural network and the genetic algorithm. The modified neural network exhibits a node-to-node relationship which enhances its learning and generalization abilities. A digit-and-command interpreter constructed by the modified neural networks is proposed to recognize handwritten digits and commands. A genetic algorithm is employed to train the parameters of the modified neural networks of the digit-and-command interpreter. The proposed digit-and-command interpreter is successfully realized in an electronic book. Simulation and experimental results will be presented to show the applicability and merits of the proposed approach.

KW - Digit and command interpretation

KW - Electronic book

KW - Genetic algorithm

KW - Neural networks

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JO - IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

JF - IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

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ER -

Digit and command interpretation for electronic book using neural network and genetic algorithm

Abstract

UN SDGs

Keywords

ASJC Scopus subject areas

More information

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