Latent embeddings for word images and their semantics
US10635949B2 · kind B2 · utility
4Cited by
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21Claims
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Key dates
| Filing date | Jul 7, 2015 |
| Grant date | Apr 28, 2020 |
| Priority date | — |
| Expiry date | Mar 16, 2036 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V30/226
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A system and method enable semantic comparisons to be made between word images and concepts. Training word images and their concept labels are used to learn parameters of a neural network for embedding word images and concepts in a semantic subspace in which comparisons can be made between word images and concepts without the need for transcribing the text content of the word image. The training of the neural network aims to minimize a ranking loss over the training set where non relevant concepts for an image which are ranked more highly than relevant ones penalize the ranking loss.
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