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DIFFERENTIAL CLASSIFICATION USING MULTIPLE NEURAL NETWORKS

  • US 20180349742A1
  • Filed: 06/16/2017
  • Published: 12/06/2018
  • Est. Priority Date: 05/30/2017
  • Status: Active Grant
First Claim
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1. A method comprising:

  • storing a plurality of neural networks in memory, wherein each neural network of the plurality of neural networks is trained to recognize a set of confused graphemes from one or more sets of confused graphemes identified in recognition data for a plurality of document images, wherein each set of confused graphemes from the one or more sets of confused graphemes comprises a plurality of different graphemes that are graphically similar to each other;

    receiving an input grapheme image associated with a document image comprising a plurality of grapheme images;

    determining a set of recognition options for the input grapheme image, wherein the set of recognition options comprises a set of target characters that are similar to the input grapheme image;

    selecting, by a processing device, a first neural network from the plurality of neural networks, wherein the first neural network is trained to recognize a first set of confused graphemes, and wherein the first set of graphemes comprises at least a portion of the set of recognition options for the input grapheme image; and

    determining a grapheme class for the input grapheme image using the selected first neural network.

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