Transforming Art History: Team Award
Team Members: Elizabeth Bolman, Ken Singer, Michael Hinczewski, Ina Martin, Lauryn Smith, Sarah Lavin, Sam Schwab, Fang Ji, Michael McMaster, Shishir Adhikari, Marci O’Dwyer and Gundeep Singh
This interdisciplinary team is transforming art history at CWRU and around the world. The project models the potential of transdisciplinary collaboration among fields that rarely have any intersection: physics, art history and machine learning. The team is combining a longstanding art historical type of problem with bleeding edge machine learning capabilities. The project takes high resolution scans of paintings and asks the machine to identify individual artists’ hands. So far, the results are about 95% accurate. Correctly identifying artists is profoundly important for art historical research, museums, and the billion-dollar global art market. The potential for machines to replicate the work of human “connoisseurs” surely will have worldwide impact.