公开(公告)号：US11907336B2

公开(公告)日：2024-02-20

申请号：US17516948

申请日：2021-11-02

Applicant: SAP SE

Inventor： Ran M. Bittmann ,  Hans-Martin Ramsl

IPC: G06K9/62 ,  G06F18/21 ,  G06F18/214 ,  G06F18/2411 ,  G06K19/06 ,  G06V30/19

CPC classification number: G06F18/217 ,  G06F18/214 ,  G06F18/2411 ,  G06K19/06028 ,  G06K19/06037 ,  G06V30/19153

Abstract: Systems, methods, and computer-readable media are disclosed for visual labeling of training data items for training a machine learning model. Training data items may be generated for training the machine learning model. Visual labels, such as QR codes, may be created for the training data items. The creation of the training data item and the visual label may be automated. The visual labels and the training data items may be combined to obtain a labeled training data item. The labeled training data item may comprise a separator to distinguish the training data item from the visual label. The labeled training data item may be used for training and validation of the machine learning model. The machine learning model may analyze the training data item, attempt to identify the training data item, and compare the identification against the embedded label.

公开(公告)号：US20230133030A1

公开(公告)日：2023-05-04

申请号：US17516948

申请日：2021-11-02

Applicant: SAP SE

Inventor： Ran M. Bittmann ,  Hans-Martin Ramsl

IPC: G06K9/62

Abstract: Systems, methods, and computer-readable media are disclosed for visual labeling of training data items for training a machine learning model. Training data items may be generated for training the machine learning model. Visual labels, such as QR codes, may be created for the training data items. The creation of the training data item and the visual label may be automated. The visual labels and the training data items may be combined to obtain a labeled training data item. The labeled training data item may comprise a separator to distinguish the training data item from the visual label. The labeled training data item may be used for training and validation of the machine learning model. The machine learning model may analyze the training data item, attempt to identify the training data item, and compare the identification against the embedded label.