Face Recognition with VG-RAM Weightless Neural Networks (original) (raw)

Abstract

Virtual Generalizing Random Access Memory Weightless Neural Networks (Vg-ram wnn) are effective machine learning tools that offer simple implementation and fast training and test. We examined the performance of Vg-ram wnn on face recognition using a well known face database—the AR Face Database. We evaluated two Vg-ram wnn architectures configured with different numbers of neurons and synapses per neuron. Our experimental results show that, even when training with a single picture per person, Vg-ram wnn are robust to various facial expressions, occlusions and illumination conditions, showing better performance than many well known face recognition techniques.

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Authors and Affiliations

  1. Departamento de Informática, ,
    Alberto F. De Souza, Claudine Badue, Felipe Pedroni, Stiven Schwanz Dias, Hallysson Oliveira & Soterio Ferreira de Souza
  2. Departamento de Ciência da Informação, Universidade Federal do Espírito Santo, Av. Fernando Ferrari, 514, 29075-910, Vitória-ES, Brazil
    Elias Oliveira

Authors

  1. Alberto F. De Souza
  2. Claudine Badue
  3. Felipe Pedroni
  4. Elias Oliveira
  5. Stiven Schwanz Dias
  6. Hallysson Oliveira
  7. Soterio Ferreira de Souza

Editor information

Véra Kůrková Roman Neruda Jan Koutník

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© 2008 Springer-Verlag Berlin Heidelberg

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De Souza, A.F. et al. (2008). Face Recognition with VG-RAM Weightless Neural Networks. In: Kůrková, V., Neruda, R., Koutník, J. (eds) Artificial Neural Networks - ICANN 2008. ICANN 2008. Lecture Notes in Computer Science, vol 5163. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87536-9\_97

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