公开(公告)号：US20230334309A1

公开(公告)日：2023-10-19

申请号：US17720658

申请日：2022-04-14

Applicant: SAP SE

Inventor： Alexey Streltsov ,  Monit Shah Singh ,  Dhananjay Tomar ,  Christian Reisswig ,  Minh Duc Bui

IPC: G06N3/08

CPC classification number: G06N3/08

Abstract: Systems, methods, and computer-readable media for generating a synthetic training data set from an original unstructured electronic document are disclosed. The synthetic training data set may be used to train a deep learning model to extract data from the original electronic document. The original electronic document may comprise annotated data fields. Each annotated data field may comprise a bounding box and a label. The original electronic document may comprise a header, a table, and a footer. Macro augmentation operations may be applied to the original electronic document to create sub-templates representative of distinct page layouts in the original electronic document. The synthetic training data set may be generated by applying geometric and semantic data augmentations to the sub-templates and the original electronic documents. The synthetic training data set may then be provided the deep learning model for training.