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- W3011648156 abstract "In this paper, we present an IoT application targeting food quality. We utilize the spectrometer as a ubiquitous sensor to provide a Near-infrared (NIR) spectrum that can be used to develop regression models targeting milk quality. We solve a regression problem for different milk components such as Fat, Protein, Lactose, and Solids-Non-Fat. We apply a variety of comparative configurations of regression models, pre-processing techniques, wavelength selection, and feature extraction methods. Our study shows that for the milk data, non-linear models (GPR and SVR) are better choices when compared to linear models." @default.
- W3011648156 created "2020-03-23" @default.
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- W3011648156 date "2019-11-01" @default.
- W3011648156 modified "2023-09-26" @default.
- W3011648156 title "Spectrometer as an Ubiquitous Sensor for IoT Applications Targeting Food Quality" @default.
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- W3011648156 doi "https://doi.org/10.1109/aiccsa47632.2019.9035230" @default.
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