Identification and quantification of common adulterants in extra virgin olive oil using microwave dielectric spectroscopy aided by feedforward neural networks (2024)
- Authors:
- USP affiliated authors: BORGES, BEN HUR VIANA - EESC ; ALARCON, JÚLIO CÉSAR PICOLO - EESC ; SOUZA, MATEUS ISAAC DE OLIVEIRA - EESC ; PEPINO, VINICIUS MARRARA - EESC
- Unidade: EESC
- DOI: 10.1109/JSEN.2024.3448221
- Subjects: REDES NEURAIS; ESPECTROSCOPIA; APRENDIZADO COMPUTACIONAL; AZEITE; ENGENHARIA ELÉTRICA
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher place: Piscataway, NJ
- Date published: 2024
- Source:
- Título: IEEE Sensors Journal
- ISSN: 1558-1748
- Volume/Número/Paginação/Ano: Inpress, p. 1-11, 2024
- Status:
- Artigo possui versão em acesso aberto em repositório (Green Open Access)
- Versão do Documento:
- Versão submetida (Pré-print)
- Acessar versão aberta:
-
ABNT
ALARCON, Julio C. P. et al. Identification and quantification of common adulterants in extra virgin olive oil using microwave dielectric spectroscopy aided by feedforward neural networks. IEEE Sensors Journal, p. 1-11, 2024Tradução . . Disponível em: http://dx.doi.org/10.1109/JSEN.2024.3448221. Acesso em: 02 abr. 2026. -
APA
Alarcon, J. C. P., Souza, M. I. de O., Pepino, V. M., & Borges, B. -H. V. (2024). Identification and quantification of common adulterants in extra virgin olive oil using microwave dielectric spectroscopy aided by feedforward neural networks. IEEE Sensors Journal, 1-11. doi:10.1109/JSEN.2024.3448221 -
NLM
Alarcon JCP, Souza MI de O, Pepino VM, Borges B-HV. Identification and quantification of common adulterants in extra virgin olive oil using microwave dielectric spectroscopy aided by feedforward neural networks [Internet]. IEEE Sensors Journal. 2024 ; 1-11.[citado 2026 abr. 02 ] Available from: http://dx.doi.org/10.1109/JSEN.2024.3448221 -
Vancouver
Alarcon JCP, Souza MI de O, Pepino VM, Borges B-HV. Identification and quantification of common adulterants in extra virgin olive oil using microwave dielectric spectroscopy aided by feedforward neural networks [Internet]. IEEE Sensors Journal. 2024 ; 1-11.[citado 2026 abr. 02 ] Available from: http://dx.doi.org/10.1109/JSEN.2024.3448221 - Microwave glucose sensing using double circular split ring resonators for improved sensitivity: the role of artificial blood plasma and deionized water
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