| Abstrakt: |
We propose an innovative framework for assessing the probability that a subject drawing is the work of a particular artist. While numerous efforts have applied neural networks to classify two-dimensional works of art by style and author, these efforts – with few exceptions – have been limited to paintings. Drawings, which can involve multiple media with very different visual characteristics and greater susceptibility to damage than paint, present a more formidable challenge. Our technique is robust to the age and wear of a drawing as well as the possibility that it contains marks made with multiple drawing media. We obtained classification accuracies exceeding 90% using a five-layer convolutional neural network (CNN), which we trained on a curated set of drawing images attributed to Raffaello Sanzio da Urbino (1483-1520), known as Raphael, as well as drawings by his admirers, imitators, and forgers. |
