High performance OCR with syntactic neural networks

This paper describes the application of a special type of syntactic neural network (SNN) to the recognition of hand-written digits. Importantly, it is shown that this class of SNN can be implemented to work at very high classification speeds (similar to that of an N-tuple classifier), but with higher classification accuracy when trained on enough data. Results are reported on the ESSEX and CEDAR data sets to demonstrate this.