Synthesizing hard-negative text training data
US11948382B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 18, 2020 |
| Grant date | Apr 2, 2024 |
| Priority date | — |
| Expiry date | Nov 11, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method for synthesizing negative training data associated with training models to detect text within documents and images. The method includes one or more computer processors receiving a set of dictates associated with generating one or more negative training datasets for training a set of models to classify a plurality of features found within a data source. The method further includes identifying a set of rules related to generating negative training data to detect text based on the received set of dictates. The method further includes compiling one or more arrays of elements of hard-negative training data into a negative training data dataset based on the identified set of rules and one or more dictates. The method further includes determining metadata corresponding an array of elements of hard-negative training data.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.