  Edge computing is promising to become one of the next hottest topics in
artificial intelligence because it benefits various evolving domains such as
real-time unmanned aerial systems, industrial applications, and the demand for
privacy protection. This paper reviews recent advances on binary neural network
(BNN) and 1-bit CNN technologies that are well suitable for front-end,
edge-based computing. We introduce and summarize existing work and classify
them based on gradient approximation, quantization, architecture, loss
functions, optimization method, and binary neural architecture search. We also
introduce applications in the areas of computer vision and speech recognition
and discuss future applications for edge computing.
