Invention Grant
- Patent Title: Machine learning-based inference of granular font properties
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Application No.: US16854913Application Date: 2020-04-22
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Publication No.: US11610138B2Publication Date: 2023-03-21
- Inventor: Jessica Lundin , Owen Winne Schoppe , Alan Martin Ross , Brian J. Lonsdorf , David James Woodward , Sönke Rohde , Michael Reynolds Sollami , Chetan Ramaiah
- Applicant: salesforce.com, inc.
- Applicant Address: US CA San Francisco
- Assignee: salesforce.com, inc.
- Current Assignee: salesforce.com, inc.
- Current Assignee Address: US CA San Francisco
- Agency: Fenwick & West LLP
- Main IPC: G06V30/244
- IPC: G06V30/244 ; G06N5/02 ; G06F17/16 ; G06F40/109 ; G06N20/00 ; G06N5/04 ; G06T7/00

Abstract:
A textual properties model is used to infer values for certain font properties of interest given certain text-related data, such as rendered text images. The model may be used for numerous purposes, such as aiding with document layout, identifying font families that are similar to a given font families, and generating new font families with specific desired properties. In some embodiments, the model is trained from a combination of synthetic data that is labeled with values for the font properties of interest, and partially-labeled data from existing “real-world” documents.
Public/Granted literature
- US20210334666A1 MACHINE LEARNING-BASED INFERENCE OF GRANULAR FONT PROPERTIES Public/Granted day:2021-10-28
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