Handwritten characters recognition based on nature-inspired computing and neuro-evolution

The enormous services obtainable by bank and postal systems are not 100 % guaranteed due to variability of handwriting styles. Various methods based on neural networks have been suggested to address this issue. Unfortunately, they often fall into local optima that arises from the use of old learning...

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Vydané v:	Applied intelligence (Dordrecht, Netherlands) Ročník 38; číslo 2; s. 146 - 159
Hlavní autori:	Nebti, Salima, Boukerram, Abdellah
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Boston Springer US 01.03.2013 Kluwer Springer Nature B.V
Predmet:	Algorithmics. Computability. Computer arithmetics Algorithms Applied sciences Artificial Intelligence Character recognition Computer Science Computer science; control theory; systems Connectionism. Neural networks Data processing. List processing. Character string processing Exact sciences and technology Genetic algorithms Handwriting Intelligence Machines Manufacturing Mechanical Engineering Memory organisation. Data processing Networks Neural networks Optimization Pattern recognition Pattern recognition. Digital image processing. Computational geometry Processes Proposals Recognition Software Theoretical computing Neuro-evolution Bees’ algorithm Co-evolution PSO Handwritten characters recognition Bank system Bees' algorithm Image processing Evolutionary algorithm Variability Aggregate model Voting Classification Swarm intelligence Majority rule Bayes decision Local search Minimal sum algorithm Global optimum Pattern recognition Neural network Character recognition Particle swarm optimization Radial basis function Optical character recognition Optimal solution Minimax method Manuscript character Artificial intelligence
ISSN:	0924-669X, 1573-7497
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