Deep interactive learning for image segmentation models
US11682117B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 1, 2021 |
| Grant date | Jun 20, 2023 |
| Priority date | — |
| Expiry date | Nov 1, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V10/26
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Described herein are systems and methods of training models to segment images. A device may identify a training dataset. The training dataset may include images each having a region of interest. The training dataset may include first annotations. The device may train, using the training dataset, an image segmentation model having parameters to generate a corresponding first segmented images. The device may provide the first segmented images for presentation on a user interface to obtain feedback. The device may receive, via the user interface, a feedback dataset including second annotations for at least a subset of the first segmented images. Each of the second annotations may label at least a second portion of the region of interest in a corresponding image of the subset. The device may retrain, using the feedback dataset received via the user interface, the image segmentation model.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.