Invention Grant
- Patent Title: Training neural networks to perform tag-based font recognition utilizing font classification
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Application No.: US17584962Application Date: 2022-01-26
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Publication No.: US11636147B2Publication Date: 2023-04-25
- Inventor: Zhaowen Wang , Tianlang Chen , Ning Xu , Hailin Jin
- Applicant: Adobe Inc.
- Applicant Address: US CA San Jose
- Assignee: Adobe Inc.
- Current Assignee: Adobe Inc.
- Current Assignee Address: US CA San Jose
- Agency: Keller Preece PLLC
- Main IPC: G06F16/906
- IPC: G06F16/906 ; G06F16/55 ; G06N3/084 ; G06F16/903 ; G06F40/109 ; G06V30/244 ; G06F18/28 ; G06F18/21 ; G06F18/214 ; G06F18/2415 ; G06V30/19 ; G06V30/226 ; G06V10/82 ; G06V10/44

Abstract:
The present disclosure relates to a tag-based font recognition system that utilizes a multi-learning framework to develop and improve tag-based font recognition using deep learning neural networks. In particular, the tag-based font recognition system jointly trains a font tag recognition neural network with an implicit font classification attention model to generate font tag probability vectors that are enhanced by implicit font classification information. Indeed, the font recognition system weights the hidden layers of the font tag recognition neural network with implicit font information to improve the accuracy and predictability of the font tag recognition neural network, which results in improved retrieval of fonts in response to a font tag query. Accordingly, using the enhanced tag probability vectors, the tag-based font recognition system can accurately identify and recommend one or more fonts in response to a font tag query.
Public/Granted literature
- US20220148325A1 TRAINING NEURAL NETWORKS TO PERFORM TAG-BASED FONT RECOGNITION UTILIZING FONT CLASSIFICATION Public/Granted day:2022-05-12
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