公开(公告)号：US20220092405A1

公开(公告)日：2022-03-24

申请号：US17025845

申请日：2020-09-18

Applicant: SAP SE

Inventor： Matthias Frank ,  Hoang-Vu Nguyen ,  Stefan Klaus Baur ,  Alexey Streltsov ,  Jasmin Mankad ,  Cordula Guder ,  Konrad Schenk ,  Philipp Lukas Jamscikov ,  Rohit Kumar Gupta

IPC: G06N3/08 ,  G06N3/04 ,  G06F16/81

Abstract: In an example embodiment, a deep neural network may be utilized to determine matches between candidate pairs of entities, as well as confidence scores that reflect how certain the deep neural network is about the corresponding match. The deep neural network is also able to find these matches without requiring domain knowledge that would be required if features for a machine-learned model were handcrafted, which is a drawback of prior art machine-learned models used to match entities in multiple tables. Thus, the deep neural network improves on the functioning of prior art machine learned models designed to perform the same tasks. Specifically, the deep neural network learns the relationships of tabular fields and the patterns that define a match from historical data alone, making this approach generic and applicable independent of the context.

公开(公告)号：US20220019849A1

公开(公告)日：2022-01-20

申请号：US16932130

申请日：2020-07-17

Applicant: SAP SE

Inventor： Sohyeong Kim ,  Ying Jiang ,  Cordula Guder

IPC: G06K9/62 ,  G06K9/00 ,  G06N20/00 ,  G06T7/90 ,  G06F16/535

Abstract: Methods, systems, and articles of manufacture, including computer program products, are provided for synthesizing images for machine learning. The method may include selecting one or more image preprocessing transformations to apply on the foreground object image; applying the selected one or more image preprocessing transformations to the foreground object image; selecting a background image from a set of background images depicting a variety of different backgrounds which may be associated with the foreground object image; merging the selected background image with the foreground object image to form a synthesized image; selecting one or more image transformations to apply on the synthesized image; applying the selected one or more image transformations to the synthesized image; and storing the synthesized image in a collection of synthesized images to train a machine learning model.

公开(公告)号：US11531837B2

公开(公告)日：2022-12-20

申请号：US16932130

申请日：2020-07-17

Applicant: SAP SE

Inventor： Sohyeong Kim ,  Ying Jiang ,  Cordula Guder

IPC: G06K9/62 ,  G06K9/00 ,  G06F16/535 ,  G06N20/00 ,  G06T7/90

Abstract: Methods, systems, and articles of manufacture, including computer program products, are provided for synthesizing images for machine learning. The method may include selecting one or more image preprocessing transformations to apply on the foreground object image; applying the selected one or more image preprocessing transformations to the foreground object image; selecting a background image from a set of background images depicting a variety of different backgrounds which may be associated with the foreground object image; merging the selected background image with the foreground object image to form a synthesized image; selecting one or more image transformations to apply on the synthesized image; applying the selected one or more image transformations to the synthesized image; and storing the synthesized image in a collection of synthesized images to train a machine learning model.