Artificial neural networks applied to the classification of hair samples according to pigment and sex using non-invasive analytical techniques

Autor(es)

Berto, Tamires Messias ; Santos, Monica Cardoso ; Pereira, Fabiola Manhas Verbi ; Filletti, Erica Regina

• Tipo de documento: Artigo Científico
• Fonte: X-RAY SPECTROMETRY; v. 49, n. 6, p. 10-pg., 2020-06-09.

Resumo

In this study, we investigated the possibility of using an artificial neural network (ANN) to classify human hair samples according to pigment (original or bleached hair) and sex (female or male) from numerical data obtained by wavelength dispersive X-ray fluorescence (WDXRF) and by laser-induced breakdown spectroscopy (LIBS). The results were promising, showing that the developed ANNs are able to classify the pigment and donor sex of hair samples with 100% and 89.5% accuracy, respectively, in the test set using WDXRF data. For the LIBS data in the test set, 100% of the pigment classifications were correct, and 78.9% of the donor sex classifications were correct. (AU)

• Processo FAPESP: 19/01102-8 - EMU concedido no processo 2018/18212-8: espectrômetro de fluorescência de Raios-X
• Beneficiário: Fabiola Manhas Verbi Pereira
• Modalidade de apoio: Auxílio à Pesquisa - Programa Equipamentos Multiusuários
• Processo FAPESP: 18/18212-8 - Desenvolvimento de modelos quimiométricos para determinação de impurezas sólidas na matéria prima cana-de-açúcar utilizando o potencial da fluorescência de raios-X por energia dispersiva
• Beneficiário: Fabiola Manhas Verbi Pereira
• Modalidade de apoio: Auxílio à Pesquisa - Regular