公开(公告)号：US20210117666A1

公开(公告)日：2021-04-22

申请号：US16655363

申请日：2019-10-17

Applicant: Adobe Inc.

Inventor： Verena Sabine Kaynig-Fittkau ,  Smitha Bangalore Naresh ,  Shawn Alan Gaither ,  Richard Cohn ,  Paul John Asente ,  Eylon Stroh ,  Emily Seminerio

IPC: G06K9/00 ,  G06N20/00

Abstract: Techniques are provided for identifying structural elements of a document. One Methodology includes generating a first channel of rasterized content by rasterizing a full page of the document and generating one or more additional channels of rasterized content from the page of the document by rasterizing one or more corresponding content types from the page of the document. Each of the one or more additional channels includes a specific type of content that is different from each of the other one or more additional channels. The methodology further includes inputting the first channel of rasterized content and the one or more additional channels of rasterized content into a machine learning (ML) model. The methodology continues with determining location and classification for each of a plurality of structural elements on the page of the document using the ML model.

公开(公告)号：US11386685B2

公开(公告)日：2022-07-12

申请号：US16655363

申请日：2019-10-17

Applicant: Adobe Inc.

Inventor： Verena Sabine Kaynig-Fittkau ,  Smitha Bangalore Naresh ,  Shawn Alan Gaither ,  Richard Cohn ,  Paul John Asente ,  Eylon Stroh ,  Emily Seminerio

IPC: G06V30/413 ,  G06N20/00 ,  G06V30/412 ,  G06V30/414

Abstract: Techniques are provided for identifying structural elements of a document. One Methodology includes generating a first channel of rasterized content by rasterizing a full page of the document and generating one or more additional channels of rasterized content from the page of the document by rasterizing one or more corresponding content types from the page of the document. Each of the one or more additional channels includes a specific type of content that is different from each of the other one or more additional channels. The methodology further includes inputting the first channel of rasterized content and the one or more additional channels of rasterized content into a machine learning (ML) model. The methodology continues with determining location and classification for each of a plurality of structural elements on the page of the document using the ML model.