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.