A framework for predicting odor threshold values of perfumes by scientific machine learning and transfer learning

Knowledge of odor thresholds is very important for the perfume industry. Due to the difficulty associated with measuring odor thresholds, empirical models capable of estimating these values can be an invaluable contribution to the field. This work developed a framework based on scientific machine le...

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Detalles Bibliográficos
Autores principales: Oliveira, Luis M.C., Santana, Vinícius V., Rodrigues, Alírio E., Ribeiro, Ana M., B. R. Nogueira, Idelfonso
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10589844/
https://www.ncbi.nlm.nih.gov/pubmed/37867888
http://dx.doi.org/10.1016/j.heliyon.2023.e20813

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10589844/
https://www.ncbi.nlm.nih.gov/pubmed/37867888
http://dx.doi.org/10.1016/j.heliyon.2023.e20813

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