изследване

Researchers train AI to attribute paintings based on detailed brushstroke analysis

A figure from the research paper "Discerning the painter’s hand: machine learning on surface topography" showing four paintings analysed in row A, topographic data in row B and machine learning attributions of different areas of each canvas in row C
photo: Case Western Reserve University

Art historians may have a new tool for settling the attribution of disputed paintings using artificial intelligence (AI) thanks to research by a cross-disciplinary team led by physicists at Case Western Reserve University in Cleveland, Ohio. The research, published in November in the journal Heritage Science, shows how machine learning analysis of small sections of topographical scans of paintings—some as tiny as half a millimeter—was able to attribute the works to the correct artist with up to 96% accuracy.

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