Paper

Reading checks with multilayer graph transformer networks

We propose a new machine learning paradigm called multilayer graph transformer network that extends the applicability of gradient-based learning algorithms to systems composed of modules that take graphs as input and produce graphs as output. A complete check reading system based on this concept is described. The system combines convolutional neural network character recognizers with graph-based stochastic models trained cooperatively at the document level. It is deployed commercially and reads million of business and personal checks per month with record accuracy.

Authors: Yann Le Cun · L. Bottou · Y. Bengio

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