Classification of Coffee and Wine with a Microwave Resonator and Deep Learning Machine Technique

12 June 2020, Version 1
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

In this study, coffee and wine were measured using an microwave resonator, and a deep learning system was trained using the acquired data, and then tested to see if the deep leaning system could distinguish these samples. We tested 6 kinds of wine, 6 kinds of cold brew coffee and 6 kinds of bottled coffee. The microwave resonance spectra of all samples were graphically displayed. The graphical images were processed by an artificial intelligence (AI) technique. By applying deep learning machine technique instead of the peak assignment for complex compounds in general, it was possible to facilitate the classification of coffee or wine with high accuracy.

Keywords

Classification
microwave resonator
AI
Coffee
Wine

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