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A Machine Learning Method for the Quantitative Detection of Adulterated Meat Using a MOS-Based E-Nose
Meat adulteration is a global problem which undermines market fairness and harms people with allergies or certain religious beliefs. In this study, a novel framework in which a one-dimensional convolutional neural network (1DCNN) serves as a backbone and a random forest regressor (RFR) serves as a r...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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MDPI
2022
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8870927/ https://www.ncbi.nlm.nih.gov/pubmed/35206078 http://dx.doi.org/10.3390/foods11040602 |