<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The process of pattern recognition in the biometrics is particularly important. The patterns can differ from each other a lot, and even the samples can be significantly different from the templates. The Artificial Neural Networks can be applied as a universal approximator to recognize the patterns with more flexibility. However the topology of the networks determines the processing time and complexity of the hardware of the physical environments. The Genetic Algorithms can be used with success in optimization problems like in this situation, the topology of the neural network is more optimal if we apply the Genetic Algorithms. This study introduce an algorithm in which a tailor made algorithm correcting the topology to enhance the effectiveness of the process.</p></abstract>

The process of pattern recognition in the biometrics is particularly important. The patterns can differ from each other a lot, and even the samples can be significantly different from the templates. The Artificial Neural Networks can be applied as a universal approximator to recognize the patterns with more flexibility. However the topology of the networks determines the processing time and complexity of the hardware of the physical environments. The Genetic Algorithms can be used with success in optimization problems like in this situation, the topology of the neural network is more optimal if we apply the Genetic Algorithms. This study introduce an algorithm in which a tailor made algorithm correcting the topology to enhance the effectiveness of the process.

Optimization of Artificial Neural Networks with Genetic Algorithms for Biometric Pattern Recognition

Land Forces Academy Review

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

The process of pattern recognition in the biometrics is particularly important. The patterns can differ from each other a lot, and even the samples can be...

Optimization of Artificial Neural Networks with Genetic Algorithms for Biometric Pattern Recognition

Data publikacji: 23 paź 2019

Zakres stron: 256 - 264

DOI: https://doi.org/10.2478/raft-2019-0031

Słowa kluczowe
biometrics, artificial neural networks, genetic algorithm, pattern recognition, soft-computing, deep-learning

© 2019 Gábor Werner et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Optimization of Artificial Neural Networks with Genetic Algorithms for Biometric Pattern Recognition

Data publikacji: 23 paź 2019

Zakres stron: 256 - 264

DOI: https://doi.org/10.2478/raft-2019-0031

Słowa kluczowebiometrics, artificial neural networks, genetic algorithm, pattern recognition, soft-computing, deep-learning

© 2019 Gábor Werner et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Słowa kluczowe
biometrics, artificial neural networks, genetic algorithm, pattern recognition, soft-computing, deep-learning