Method and device for training generative adversarial network for converting between heterogeneous domain data
US12417541B2 · kind B2 · utility
Assignees
Inventors
Key dates
| Filing date | Oct 28, 2020 |
| Grant date | Sep 16, 2025 |
| Priority date | — |
| Expiry date | Oct 10, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V20/695
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Provided is a method of training a generative adversarial network (GAN) for converting between heterogeneous domains, the method including training a first GAN and a second GAN with at least one unpaired training data set comprised of a training image of a first domain and a training image of a second domain; using the trained first GAN to convert a first image of the first domain to an image of the second domain; using the trained second GAN to reconvert the converted image of the second domain to a second image of the first domain; and performing segmentation on at least one of the first image of the first domain, the converted image of the second domain, or the reconverted second image of the first domain.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.