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Coffee Flavor Prediction – Application of Machine and Deep Learning Methods on Near-Infrared Spectra
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This work aimed to predict specialty coffee flavors using machine and deep learning methods on near-infrared spectra.
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The developed models could provide flavor prediction for seven categories with the performance of recall above 70% and accuracy above 72%.
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The method of focusing plot could visualize the attention of the deep convolutional neural network and explain the decisive feature bands for predicting the coffee flavors.
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The feasibility of applying a very deep convolutional neural network on NIR spectra and multi-labeled data were demonstrated.
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