Font recognition using triplet loss neural network training
US10515295B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 27, 2017 |
| Grant date | Dec 24, 2019 |
| Priority date | — |
| Expiry date | Jul 11, 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 to jointly 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 can jointly train a font recognition neural network using a font classification loss model and triplet loss model to generate a deep learning neural network that provides improved font classifications. In addition, the font recognition system can employ the trained font recognition neural network to efficiently recognize fonts within input images as well as provide other suggested fonts.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.