Computer-Aided Visual Inspection of Glass-Coated Tableware Ceramics for Multi-Class Defect Detection
Quality control procedures in the manufacturing of tableware ceramics require a demanding, monotonous, subjective, and faulty human manual inspection.This paper presents two machine learning strategies and the results of a semi-automated visual inspection of ceramics tableware applied to a private dataset acquired during the VAICeramics project.In