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Patent Searching and Data


Title:
DATA EXTRACTION PIPELINE
Document Type and Number:
WIPO Patent Application WO/2019/138074
Kind Code:
A1
Abstract:
A computer-implemented method for classifying a document type of a document in an image and extracting data from the classified document comprising acquiring image data that comprises data relating to at least a part of the document. Textual classification of the document image is then attempted by machine recognition of textual characters to obtain classification data; and using the classification data to classify the document in the image.

Inventors:
CALI JACQUES (GB)
ROELANTS PETER (GB)
SAGONAS CHRISTOS (GB)
SABATHE ROMAIN (GB)
Application Number:
EP2019/050693
Publication Date:
July 18, 2019
Filing Date:
January 11, 2019
Export Citation:
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Assignee:
ONFIDO LTD (GB)
International Classes:
G06K9/00
Foreign References:
US20130287284A12013-10-31
EP2845147A12015-03-11
US20020037097A12002-03-28
EP1439485A12004-07-21
US20160125613A12016-05-05
US20100293180A12010-11-18
Other References:
ADAM W HARLEY ET AL: "Evaluation of Deep Convolutional Nets for Document Image Classification and Retrieval", ARXIV.ORG, CORNELL UNIVERSITY LIBRARY, 201 OLIN LIBRARY CORNELL UNIVERSITY ITHACA, NY 14853, 25 February 2015 (2015-02-25), XP080804130
JONATHAN LONG ET AL: "Fully convolutional networks for semantic segmentation", 2015 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), vol. abs/1411.4038v2, 8 March 2015 (2015-03-08), pages 1 - 10, XP055294644, ISBN: 978-1-4673-6964-0, DOI: 10.1109/CVPR.2015.7298965
JIANFENG WANG: "Gated Recurrent Convolution Neural Network for OCR", 2 March 2017 (2017-03-02), XP055507252, Retrieved from the Internet [retrieved on 20180914]
None
Attorney, Agent or Firm:
BRUNNER, John Michael Owen et al. (One Southampton Row, London WC1B 5HA, GB)
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