System and method for training a machine-learning model to identify real-world elements
US10242264B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 25, 2018 |
| Grant date | Mar 26, 2019 |
| Priority date | — |
| Expiry date | Apr 25, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V20/58
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method and a system for training a machine-learning model to identify real-world elements using a simulated environment (SE) may include (a) receiving at least one set of appearance parameters, corresponding to appearance of real-world element; (b) generating one or more realistic elements, each corresponding to a variant of at least one real-world element; (c) generating one or more abstract-elements; (d) placing the elements within the SE; (e) producing at least one synthetic image from the SE; (f) providing the at least one synthetic image to a machine-learning model; and (g) training the machine-learning model to identify at least one real-world element from the at least one synthetic image, that corresponds to at least one realistic element in the SE.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.