The artistic style of a painting is a subtle aesthetic judgment used by art
historians for grouping and classifying artwork. The recently introduced
`neural-style' algorithm substantially succeeds in merging the perceived
artistic style of one image or set of images with the perceived content of
another. In light of this and other recent developments in image analysis via
convolutional neural networks, we investigate the effectiveness of a
`neural-style' representation for classifying the artistic style of paintings.
