Abstract
In this paper we present the application of a Modular Neural Network (MNN) for iris, ear and voice recognition for a database of 77 persons. The proposed MNN architecture with which we are working consists of three modules; iris, ear and voice. Each module is divided in other three sub modules. Each sub module contains different information, which, the first 26 individuals are considered in module 1, the following 26 individuals in module 2 and the last 25 in module 3. We considered the integration of each biometric measure separately. Later, we proceed to integrate these modules with a fuzzy integrator. Also, we performed optimization of the modular neural networks and the fuzzy integrators using genetic algorithms, and comparisons were made between optimized results and the results without optimization.
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Sánchez, D., Melin, P. (2010). Modular Neural Network with Fuzzy Integration and Its Optimization Using Genetic Algorithms for Human Recognition Based on Iris, Ear and Voice Biometrics. In: Melin, P., Kacprzyk, J., Pedrycz, W. (eds) Soft Computing for Recognition Based on Biometrics. Studies in Computational Intelligence, vol 312. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15111-8_6
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DOI: https://doi.org/10.1007/978-3-642-15111-8_6
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