A method based on rf spectral featuresfor evaluating the porosity degree in ceramic materials
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In this paper, a classification system of the degree of porosity of ceramic materials based on a Radio Frequency system is presented. The system uses methods from the machine learning field to learn patterns from spectral features measured with a circular patch antenna. Experimental results show that it is possible to indirectly get an estimate of the degree of porosity of ceramic samples getting low classification error rates.