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Machine Learning Approach to Art Authentication
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Author(s): Bryan Todd Dobbs (University of North Carolina at Charlotte, USA)and Zbigniew W. Ras (University of North Carolina at Charlotte, USA)
Copyright: 2023
Pages: 14
Source title:
Encyclopedia of Data Science and Machine Learning
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-7998-9220-5.ch089
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Abstract
The popularity of machine learning algorithms produced numerous applications in computer vision in the past 10 years. One application is art authentication, which assures that a piece of art is created by an artist. The models produced by machine learning algorithms provide an objective measure to authenticate an artist to their artwork collection. This article discusses an experiment using the residual neural network machine learning algorithm. This experiment demonstrates how a computer can distinguish between 34 and 958 artists with various degrees of confidence.
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