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公开(公告)号：US10599924B2
公开(公告)日：2020-03-24
申请号：US15656269
申请日：2017-07-21
Applicant: Adobe Inc.
Inventor： Xiao Yang , Paul Asente , Mehmet Ersin Yumer
Abstract: Disclosed systems and methods categorize text regions of an electronic document into document object types based on a combination of semantic information and appearance information from the electronic document. A page segmentation application executing on a computing device accesses textual feature representations that represent text portions in a vector space, where a set of pixels from the page is mapped to a textual feature representation. The page segmentation application generates a visual feature representation, which corresponds to an appearance of a document portion including the set of pixels, by applying a neural network to the page of the electronic document. The page segmentation application generates an output page segmentation of the electronic document by applying the neural network to the textual feature representation and the visual feature representation.
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公开(公告)号：US20200167558A1
公开(公告)日：2020-05-28
申请号：US16777258
申请日：2020-01-30
Applicant: Adobe Inc.
Inventor： Xiao Yang , Paul Asente , Mehmet Yumer
Abstract: Disclosed systems and methods categorize text regions of an electronic document into document object types based on a combination of semantic information and appearance information from the electronic document. A page segmentation application executing on a computing device provides a textual feature representation and a visual feature representation to a neural network. The application identifies a correspondence between a location of the set of pixels in the electronic document and a location of a particular document object type in an output page segmentation. The application further outputs a classification of the set of pixels as being the particular document object type based on the identified correspondence.
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公开(公告)号：US11314969B2
公开(公告)日：2022-04-26
申请号：US16777258
申请日：2020-01-30
Applicant: Adobe Inc.
Inventor： Xiao Yang , Paul Asente , Mehmet Yumer
Abstract: Disclosed systems and methods categorize text regions of an electronic document into document object types based on a combination of semantic information and appearance information from the electronic document. A page segmentation application executing on a computing device provides a textual feature representation and a visual feature representation to a neural network. The application identifies a correspondence between a location of the set of pixels in the electronic document and a location of a particular document object type in an output page segmentation. The application further outputs a classification of the set of pixels as being the particular document object type based on the identified correspondence.
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