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公开(公告)号：US12056945B2
公开(公告)日：2024-08-06
申请号：US17098902
申请日：2020-11-16
Applicant: KYOCERA DOCUMENT SOLUTIONS INC.
Inventor： Andrii Matiukhov
IPC: G06V30/19 , G06F18/20 , G06F18/21 , G06F18/214 , G06F18/40 , G06N20/00 , G06V10/40 , G06V30/416
CPC classification number: G06V30/19 , G06F18/214 , G06F18/217 , G06F18/285 , G06F18/40 , G06N20/00 , G06V10/40 , G06V30/416 , G06V2201/10
Abstract: A method performed by a computing system includes receiving, by a document data extraction system (DDES), image data associated with a document. The DDES extracts, via optical character recognition (OCR) logic of the DDES, metadata from the image data. The metadata specifies sequences of text content items and text content item features associated with each text content item of the sequences of text content items. A machine learning logic (MLL) module of the DDES determines, based on the sequences of text content items and the text content item features, one or more text content items associated with a key. The DDES communicates information that specifies the key and a corresponding value that is associated with the one or more text content items that are associated with the key to a terminal.
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公开(公告)号：US20220156490A1
公开(公告)日：2022-05-19
申请号：US17098902
申请日：2020-11-16
Applicant: KYOCERA DOCUMENT SOLUTIONS INC.
Inventor： Andrii Matiukhov
Abstract: A method performed by a computing system includes receiving, by a document data extraction system (DDES), image data associated with a document. The DDES extracts, via optical character recognition (OCR) logic of the DDES, metadata from the image data. The metadata specifies sequences of text content items and text content item features associated with each text content item of the sequences of text content items. A machine learning logic (MLL) module of the DDES determines, based on the sequences of text content items and the text content item features, one or more text content items associated with a key. The DDES communicates information that specifies the key and a corresponding value that is associated with the one or more text content items that are associated with the key to a terminal.
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公开(公告)号：US11238313B2
公开(公告)日：2022-02-01
申请号：US16559322
申请日：2019-09-03
Applicant: KYOCERA DOCUMENT SOLUTIONS INC.
Inventor： Hooman Majidzadeh Rezvani , Andrii Matiukhov , Takashi Oguma , Sang Lee , Charles Henze , Hiroshi Manabe , Christian Olmstead Holmes
Abstract: Automatic document classification using machine learning may involve receiving inputs that assign documents to classifiers, which define document classification rules for a classification model. The computing device may train the classification model using a machine learning technique that assigns each document of a second set of documents to destinations based on the document classification rules. The computing device may also receive a template design for each destination that specifies metadata to extract for a document type corresponding to documents assigned to the destination. The computing device may subsequently classifying a particular document using the classification model, which may involve assigning the particular document to a given destination of the plurality of destinations based on the document classification rules, and exporting metadata from the particular document using the template design associated with the given destination.
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公开(公告)号：US20210064866A1
公开(公告)日：2021-03-04
申请号：US16559322
申请日：2019-09-03
Applicant: KYOCERA DOCUMENT SOLUTIONS INC.
Inventor： Hooman Majidzadeh Rezvani , Andrii Matiukhov , Takashi Oguma , Sang Lee , Charles Henze , Hiroshi Manabe , Christian Olmstead Holmes
Abstract: Automatic document classification using machine learning may involve receiving inputs that assign documents to classifiers, which define document classification rules for a classification model. The computing device may train the classification model using a machine learning technique that assigns each document of a second set of documents to destinations based on the document classification rules. The computing device may also receive a template design for each destination that specifies metadata to extract for a document type corresponding to documents assigned to the destination. The computing device may subsequently classifying a particular document using the classification model, which may involve assigning the particular document to a given destination of the plurality of destinations based on the document classification rules, and exporting metadata from the particular document using the template design associated with the given destination.
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