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GANs (Generative adversarial networks) is a new AI technology that canperform deep learning with less training data and has the capability ofachieving transformation between two image sets. Using GAN we have carried outa comparison between several art sets with different art style. We haveprepared several image sets; a flower photo set (A), an art image set (B1) ofImpressionism drawings, an art image set of abstract paintings (B2), an artimage set of Chinese figurative paintings, (B3), and an art image set ofabstract images (B4) created by Naoko Tosa, one of the authors. Transformationbetween set A to each of B was carried out using GAN and four image sets (B1,B2, B3, B4) was obtained. Using these four image sets we have carried outpsychological experiment by asking subjects consisting of 23 students to fillin questionnaires. By analyzing the obtained questionnaires, we have found thefollowings. Abstract drawings and figurative drawings are clearly judged to bedifferent. Figurative drawings in West and East were judged to be similar.Abstract images by Naoko Tosa were judged as similar to Western abstractimages. These results show that AI could be used as an analysis tool to revealdifferences between art genres.

Learning of Art Style Using AI and Its Evaluation Based on Psychological Experiments