Artículos de revistas
Optical Classification Of Quartz Lascas By Artificial Neural Networks
Registration in:
Optical Classification Of Quartz Lascas By Artificial Neural Networks. Taylor & Francis Inc, v. 36, p. 281-287 SEP-2015.
0882-7508
WOS:000354545800001
10.1080/08827508.2014.978315
Author
Fujiwara
Eric; Marques Dos Santos
Murilo Ferreira; Schenkel
Egont Alexandre; Ono
Eduardo; Suzuki
Carlos Kenichi
Institutions
Abstract
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) A gradation method based on quartz lascas (lumps) transparency level is proposed. The samples were irradiated by transmitting light, and the images histograms were processed by artificial neural networks. Additionally, the results were compared to conventional classification methods, including density and visual analysis. The network designed with backpropagation architecture using 4 hidden layers of 10 neurons yielded to a relative error <24% in relation to manual classification, indicating a good agreement to the miners criteria. Furthermore, the implementation of competitive learning with 5 neurons resulted in correct discrimination of samples regarding their optical characteristics with a completely non-subjective approach. 36 5
281 287 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)