Font recognition using adversarial neural network training
US10592787B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 8, 2017 |
| Grant date | Mar 17, 2020 |
| Priority date | — |
| Expiry date | Jun 27, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V30/287
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
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.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.