Invention Grant
- Patent Title: Font recognition using adversarial neural network training
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Application No.: US15807028Application Date: 2017-11-08
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Publication No.: US10592787B2Publication Date: 2020-03-17
- Inventor: Yang Liu , Zhaowen Wang , 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 Jolley Preece
- Main IPC: G06K9/68
- IPC: G06K9/68 ; G06K9/62 ; G06K9/00 ; G06N3/04 ; G06N3/08 ; G06K9/66

Abstract:
The present disclosure relates to a font recognition system that employs a multi-task learning framework and adversarial training to improve font classification and remove negative side effects caused by intra-class variances of glyph content. For example, in one or more embodiments, the font recognition system adversarial trains a font recognition neural network by minimizing font classification loss while at the same time maximizing glyph classification loss. By employing an adversarially trained font classification neural network, the font recognition system can improve overall font recognition by removing the negative side effects from diverse glyph content.
Public/Granted literature
- US20190138860A1 FONT RECOGNITION USING ADVERSARIAL NEURAL NETWORK TRAINING Public/Granted day:2019-05-09
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