Generative adversarial networks for image segmentation
US11935243B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 7, 2019 |
| Grant date | Mar 19, 2024 |
| Priority date | — |
| Expiry date | Feb 19, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30256
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method is provided of training a generative adversarial network for performing semantic segmentation of images. The generative adversarial network includes a generator neural network and a discriminator neural network. The method includes providing an image as input to the generator neural network, receiving a predicted segmentation map for the image from the generator neural network, providing i) the image, ii) the predicted segmentation map, and iii) ground-truth label data corresponding to the image, as distinct training inputs to the discriminator neural network, determining a set of one or more outputs from the discriminator neural network in response to said training inputs, and training the generator neural network using a loss function that is a function of said set of outputs from the discriminator neural network.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.