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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 machinedoi:10.26434/chemrxiv.12458252 fatcat:mw7os4cukzdkxfzj5b5dbitziy