Fuzzy ARTMAP based neural networks on the GPU for high-performance pattern recognition

Authors:
M. Martínez-Zarzuela;F. J. Díaz-Pernas;A. Tejero de Pablos;F. Perozo-Rondón;M. Antón-Rodríguez;D. González-Ortega
Affiliations:
Higher School of Telecommunications Engineering, Paseo de Belén, Valladolid, Spain;Higher School of Telecommunications Engineering, Paseo de Belén, Valladolid, Spain;Higher School of Telecommunications Engineering, Paseo de Belén, Valladolid, Spain;Higher School of Telecommunications Engineering, Paseo de Belén, Valladolid, Spain;Higher School of Telecommunications Engineering, Paseo de Belén, Valladolid, Spain;Higher School of Telecommunications Engineering, Paseo de Belén, Valladolid, Spain
Venue:
IWINAC'11 Proceedings of the 4th international conference on Interplay between natural and artificial computation: new challenges on bioinspired applications - Volume Part II
Year:
2011

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Abstract

In this paper we introduce, to the best of our knowledge, the first adaptation of the Fuzzy ARTMAP neural network for its execution on a GPU, together with a self-designed neural network based on ART models called SOON. The full VisTex database, containing 167 texture images, is proved to be classified in a very short time using these GPU-based neural networks. The Fuzzy ARTMAP neural network implemented on the GPU performs up to ×100 times faster than the equivalent CPU version, while the SOON neural network is speeded-up by ×70 times. Also, using the same texture patterns the Fuzzy ARTMAP neural network obtains a success rate of 48% and SOON of 82% for texture classification.