1. A non-transitory computer storage medium comprising computer-useable instructions that, when used by one or more computing devices, cause the one or more computing devices to perform operations comprising: receiving one or more text images, each of the one or more text images including a corresponding font label; synthesizing the one or more text images to introduce variances in the one or more text images; generating one or more training images that include the variances; cropping the one or more training images into training patches that are utilized as an input to a convolutional neural network (CNN); training the CNN with the training patches, the CNN comprising a plurality of convolutional layers and a plurality of fully connected layers; and producing a distribution of classified text images.
1. A non-transitory computer storage medium comprising computer-useable instructions that, when used by one or more computing devices, cause the one or more computing devices to perform operations comprising: receiving one or more text images, each of the one or more text images including a corresponding font label; synthesizing the one or more text images to introduce variances in the one or more text images; generating one or more training images that include the variances; cropping the one or more training images into training patches that are utilized as an input to a convolutional neural network (CNN); training the CNN with the training patches, the CNN comprising a plurality of convolutional layers and a plurality of fully connected layers; and producing a distribution of classified text images. 5. The non-transitory computer storage medium of claim 1 , wherein synthesizing the one or more text images includes randomly perturbing each text image of the one or more text images by an affine transformation.