  In this paper, we present a review of the recent work in deep learning
methods for user interface design. The survey encompasses well known deep
learning techniques (deep neural networks, convolutional neural networks,
recurrent neural networks, autoencoders, and generative adversarial networks)
and datasets widely used to design user interface applications. We highlight
important problems and emerging research frontiers in this field. We believe
that the use of deep learning for user interface design automation tasks could
be one of the high potential fields for the advancement of the software
development industry.
