非定型文書から構造化情報を抽出するディープラーニングに基づいた方法及びシステム

Title:

非定型文書から構造化情報を抽出するディープラーニングに基づいた方法及びシステム

Document Type and Number:

Japanese Patent JP7393509

Kind Code:

B2

Abstract:

To provide a deep learning-based method of extracting structured information from an atypical document, which is implemented by at least one processor of a computing device.SOLUTION: A deep learning-based method of extracting structured information from an atypical document is provided, the method comprising receiving an input image, extracting a token sequence indicative of a structure of the input image from the input image using a deep learning-based encoder-decoder model, and converting the token sequence into structured information.SELECTED DRAWING: Figure 1

More Like This:

WO/2023/147122	METHODS, SYSTEMS, ARTICLES OF MANUFACTURE AND APPARATUS TO IMPROVE TAGGING ACCURACY
WO/2023/212232	SYSTEM AND METHOD FOR DETECTING AN ADDRESS BLOCK AND BARCODE ON A CAPTURED IMAGE OF ITEM, AND READING THE DETECTED BARCODE USING CONNECTED COMPONENT ANALYSIS

Inventors:

Kim Ki Wook
Hong Tae-gyu
Lim Moonbin
Park Seung-hyun

Application Number:

JP2022189082A

Publication Date:

December 06, 2023

Filing Date:

November 28, 2022

Export Citation:

Click for automatic bibliography generation Help

Assignee:

NAVER Corporation

International Classes:

G06V30/416; G06F40/137; G06F40/14; G06N3/0455; G06N3/0464; G06N3/0475; G06T7/00; G06V10/82; G06V30/412

Domestic Patent References:

JP2020166658A
JP2020140495A
JP2021081933A
JP2019082814A

Foreign References:

US20190050640

Other References:

M. Pourreza et al., "Persian OCR with Cascaded Convolutional Neural Networks Supported by Language Model",2020 10th International Conference on Computer and Knowledge Engineering (ICCKE),米国,IEEE,2020年10月29日,pp.227-232

Attorney, Agent or Firm:

Tadashige Ito
Tadahiko Ito
Osamu Miyazaki

Previous Patent: Channel design support device and channel design support program

Next Patent: Enhancement concept of parallel encoding function