Reading checks with multilayer graph transformer networks
نویسندگان
چکیده
Yann Le Cun L eon Bottou Yoshua Bengio Speech and Image Processing Services Research Lab AT&T Labs, 101 Crawfords Corner Road, Holmdel, NJ 07733, USA [email protected] ABSTRACT 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.
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