“Since the advancement of handwritten text to typefaces on a computer, the human mind has evolved towards corresponding various typefaces as norms of comprehension. … Currently, the PANOSE system, developed in 1998, is the most widely used and accepted method for classifying typefaces based on 10 visual attributes. In this work, we employ Disentangled Beta-VAE’s, in an unsupervised learning approach, to map the latent feature space with a dataset of MNIST Style Typographic Images (TMNIST-Digit) of 0-9 digits across 2990 unique font styles.”

Find the paper and full list of authors at Open Review.