Generative adversarial network for generating images
US12141700B2 · kind B2 · utility
Assignee
Inventor
Key dates
| Filing date | Sep 17, 2020 |
| Grant date | Nov 12, 2024 |
| Priority date | — |
| Expiry date | Sep 14, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/20
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A generative adversarial network, a method of training a generator neural network, and a method of generating images using the generator network is provided. The generator neural network is configured to process an input comprising a noise vector and a pair of conditioning variables to generate an image according to the conditioning variables. The generator neural network includes a mixed-conditional batch normalization layer. The mixed-conditional batch normalization layer is configured to normalize a network layer output to generate a normalized network layer output, comprising transforming the network layer output in accordance with mixed-conditional batch normalization layer parameters to generate the normalized network layer output, wherein the mixed-conditional batch normalization layer parameters are computed by applying an affine transformation to the conditioning variables.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.