Abstract
This chapter describes the application of modular neural network architecture to improve the recognition of persons using Ear images as a biometric measure [80]. The database used was obtained from the University of Science and Technology Beijing (USTB). We show the results obtained with the modular neural network, its optimization using genetic algorithms and their integration using different methods: Winner Takes All (WTA), type-1 fuzzy integration and fuzzy integration optimized by genetic algorithms. The behavior of the simulations shows a good identification, using the appropriate pre-processing, fuzzy integrators and the best structure found by the genetic algorithm.
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© 2012 Springer-Verlag Berlin Heidelberg
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Melin, P. (2012). Optimization of Neural Networks for the Accurate Identification of Persons by Images of the Human Ear as Biometric Measure. In: Modular Neural Networks and Type-2 Fuzzy Systems for Pattern Recognition. Studies in Computational Intelligence, vol 389. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24139-0_13
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DOI: https://doi.org/10.1007/978-3-642-24139-0_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-24138-3
Online ISBN: 978-3-642-24139-0
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