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US Patent 10387531 Processing structured documents using convolutional neural networks

Patent 10387531 was granted and assigned to Google on August, 2019 by the United States Patent and Trademark Office.

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Patent abstractTimelineTable: Further ResourcesReferences
Is a
Patent
Patent

Patent attributes

Patent Applicant
Google
Google
Current Assignee
Google
Google
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
10387531
Date of Patent
August 20, 2019
Patent Application Number
14829525
Date Filed
August 18, 2015
Patent Citations Received
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US Patent 11423284 Subgraph tile fusion in a convolutional neural network
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US Patent 11048933 Generating structured representations of forms using machine learning
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US Patent 11380116 Automatic delineation and extraction of tabular data using machine learning
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US Patent 11521405 Generating structured representations of forms using machine learning
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US Patent 11550871 Processing structured documents using convolutional neural networks
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US Patent 10725748 Extracting program features for assisting software development
Patent Primary Examiner
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Paulinho E Smith
Patent abstract

Structured documents are processed using convolutional neural networks. One of the methods includes receiving a rendered form of a structured document; mapping a grid of cells to the rendered form; assigning a respective numeric embedding to each cell in the grid, comprising, for each cell: identifying content in the structured document that corresponds to a portion of the rendered form that is mapped to the cell, mapping the identified content to a numeric embedding for the identified content, and assigning the numeric embedding for the identified content to the cell; generating a matrix representation of the structured document from the numeric embeddings assigned to the cells of the grids; and generating neural network features of the structured document by processing the matrix representation of the structured document through a subnetwork comprising one or more convolutional neural network layers.

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