公开(公告)号：US10885385B2

公开(公告)日：2021-01-05

申请号：US16357720

申请日：2019-03-19

Applicant: SAP SE

Inventor： Sohyeong Kim ,  Eduardo Vellasques ,  Urko Sanchez Sanz

IPC: G06K9/00 ,  G06K9/62 ,  G06F16/532 ,  G06F16/56 ,  G06N3/08

Abstract: Disclosed herein are system, method, and computer program product embodiments for providing an image search training system. An embodiment operates by determining a query image on which to train an image search system, and a positive image visually similar to the query image. A set of negative images from a plurality of negative images visually dissimilar to the query image are selected, where the selected set of negative images includes both a first negative image and a second negative image. A first similarity measure between the first negative image and the positive image, and a second similarity measure between the second negative image and the positive image are calculated. The first negative image is selected based on the first similarity measure being less than the second similarity measure. The query image, the positive image, and the first negative image are provided to the image search system for training.

公开(公告)号：US20240289557A1

公开(公告)日：2024-08-29

申请号：US18113903

申请日：2023-02-24

Applicant: SAP SE

Inventor： Eduardo Vellasques ,  Xiang Yu ,  Stefan Klaus Baur ,  Manuel Zeise

IPC: G06F40/40 ,  G06F16/33 ,  G06F40/284

CPC classification number: G06F40/40 ,  G06F16/3347 ,  G06F40/284

Abstract: Systems and methods are provided for automated identification of key-value pairs in documents. A document including readable text is received. The document is processed to determine, from the readable text, a plurality of tokens. Pairs of vectors corresponding to the plurality of tokens are determined, each pair of vectors comprising a query vector and a key vector. Attention scores are determined for the plurality of tokens by using the pairs of vectors. The attention scores are normalized to generate normalized attention scores. Connected tokens are identified in the plurality of tokens using the normalized attention scores.

公开(公告)号：US10824808B2

公开(公告)日：2020-11-03

申请号：US16196153

申请日：2018-11-20

Applicant: SAP SE

Inventor： Christian Reisswig ,  Eduardo Vellasques ,  Sohyeong Kim ,  Darko Velkoski ,  Hung Tu Dinh

IPC: G10L15/02 ,  G06F40/295 ,  G06F40/289 ,  G06N3/04 ,  G06N3/08 ,  G06F40/30

Abstract: Disclosed herein are system, method, and computer program product embodiments for robust key value extraction. In an embodiment, one or more hierarchical concepts units (HCUs) may be configured to extract key value and hierarchical information from text inputs. The HCUs may use a convolutional neural network, a recurrent neural network, and feature selectors to analyze the text inputs using machine learning techniques to extract the key value and hierarchical information. Multiple HCUs may be used together and configured to identify different categories of hierarchical information. While multiple HCUs may be used, each may use a skip connection to transmit extracted information to a feature concatenation layer. This allows an HCU to directly send a concept that has been identified as important to the feature concatenation layer and bypass other HCUs.

公开(公告)号：US20200302229A1

公开(公告)日：2020-09-24

申请号：US16357720

申请日：2019-03-19

Applicant: SAP SE

Inventor： Sohyeong Kim ,  Eduardo Vellasques ,  Urko Sanchez Sanz

IPC: G06K9/62 ,  G06F16/532 ,  G06F16/56 ,  G06N3/08

Abstract: Disclosed herein are system, method, and computer program product embodiments for providing an image search training system. An embodiment operates by determining a query image on which to train an image search system, and a positive image visually similar to the query image. A set of negative images from a plurality of negative images visually dissimilar to the query image are selected, where the selected set of negative images includes both a first negative image and a second negative image. A first similarity measure between the first negative image and the positive image, and a second similarity measure between the second negative image and the positive image are calculated. The first negative image is selected based on the first similarity measure being less than the second similarity measure. The query image, the positive image, and the first negative image are provided to the image search system for training.