Machine learning to support geographical origin traceability of Coffea arabica (2022)
- Authors:
- USP affiliated authors: FERNANDES, ELISABETE APARECIDA DE NADAI - CENA ; SARRIES, GABRIEL ADRIAN - ESALQ ; BACCHI, MARCIO ARRUDA - CENA ; MAZOLA, YUNIEL TEJEDA - CENA ; FURLAN, GUSTAVO NAZATO - Interunidades em Ecologia Aplicada
- Unidades: CENA; ESALQ; Interunidades em Ecologia Aplicada
- DOI: 10.54364/AAIML.2022.1118
- Subjects: APRENDIZADO COMPUTACIONAL; CAFÉ; DENOMINAÇÃO DE ORIGEM
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Advances in Artificial Intelligence and Machine Learning. Research
- Volume/Número/Paginação/Ano: v. 2, n. 1, p. 273-287, 2022
- Este periódico é de assinatura
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: bronze
-
ABNT
FERNANDES, Elisabete A. De Nadai et al. Machine learning to support geographical origin traceability of Coffea arabica. Advances in Artificial Intelligence and Machine Learning. Research, v. 2, n. 1, p. 273-287, 2022Tradução . . Disponível em: https://doi.org/10.54364/AAIML.2022.1118. Acesso em: 29 dez. 2025. -
APA
Fernandes, E. A. D. N., Sarries, G. A., Mazola, Y. T., Lima, R. C., Furlan, G. N., & Bacchi, M. A. (2022). Machine learning to support geographical origin traceability of Coffea arabica. Advances in Artificial Intelligence and Machine Learning. Research, 2( 1), 273-287. doi:10.54364/AAIML.2022.1118 -
NLM
Fernandes EADN, Sarries GA, Mazola YT, Lima RC, Furlan GN, Bacchi MA. Machine learning to support geographical origin traceability of Coffea arabica [Internet]. Advances in Artificial Intelligence and Machine Learning. Research. 2022 ; 2( 1): 273-287.[citado 2025 dez. 29 ] Available from: https://doi.org/10.54364/AAIML.2022.1118 -
Vancouver
Fernandes EADN, Sarries GA, Mazola YT, Lima RC, Furlan GN, Bacchi MA. Machine learning to support geographical origin traceability of Coffea arabica [Internet]. Advances in Artificial Intelligence and Machine Learning. Research. 2022 ; 2( 1): 273-287.[citado 2025 dez. 29 ] Available from: https://doi.org/10.54364/AAIML.2022.1118 - Pet food categorization by neutron activation analysis and data science
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Informações sobre o DOI: 10.54364/AAIML.2022.1118 (Fonte: oaDOI API)
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