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The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Patent No.:

US 11816165 B1

PDFFull Text
Date of Patent:
Nov. 14, 2023

Filed:

Nov. 22, 2019

Identification of fields in documents with neural networks without templates

Applicant:

Abbyy Development Inc., Dover, DE (US);

Inventor:

Stanislav Semenov, Moscow, RU;

Assignee:

ABBYY Development Inc., Dover, DE (US);

Attorney:

Lowenstein Sandler LLP

Primary Examiner:

Edwin S Leland, III

Int. Cl.
CPC ...
G06F 16/93 (2019.01); G06F 9/30 (2018.01); G06N 3/08 (2023.01); G06V 30/224 (2022.01); G06F 16/335 (2019.01); G06F 40/279 (2020.01); G06V 10/762 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06V 30/412 (2022.01); G06F 18/23 (2023.01); G06F 18/24 (2023.01); G06F 18/232 (2023.01); G06F 18/2413 (2023.01); G06V 30/10 (2022.01);
U.S. Cl.
CPC ...
G06F 16/93 (2019.01); G06F 9/30036 (2013.01); G06F 16/335 (2019.01); G06F 18/23 (2023.01); G06F 18/232 (2023.01); G06F 18/2413 (2023.01); G06F 18/24765 (2023.01); G06F 40/279 (2020.01); G06N 3/08 (2013.01); G06V 10/763 (2022.01); G06V 10/764 (2022.01); G06V 10/765 (2022.01); G06V 10/82 (2022.01); G06V 30/224 (2022.01); G06V 30/412 (2022.01); G06V 30/10 (2022.01);
Abstract

Aspects of the disclosure provide for mechanisms for identification of fields in documents using neural networks. A method of the disclosure includes obtaining a layout of a document, the document having a plurality of fields, identifying the document, based on the layout, as belonging to a first type of documents of a plurality of identified types of documents, identifying a plurality of symbol sequences of the document, and processing, by a processing device, the plurality of symbol sequences of the document using a first neural network associated with the first type of documents to determine an association of a first field of the plurality of fields with a first symbol sequence of the plurality of symbol sequences of the document.

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