  In the realm of multimodal communication, sign language is, and continues to
be, one of the most understudied areas. In line with recent advances in the
field of deep learning, there are far reaching implications and applications
that neural networks can have for sign language interpretation. In this paper,
we present a method for using deep convolutional networks to classify images of
both the the letters and digits in American Sign Language.
