Optimized policy-based active learning for content detection
US11948387B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 8, 2021 |
| Grant date | Apr 2, 2024 |
| Priority date | — |
| Expiry date | Sep 15, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V20/20
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods for training an object detection network are described. Embodiments train an object detection network using a labeled training set, wherein each element of the labeled training set includes an image and ground truth labels for object instances in the image, predict annotation data for a candidate set of unlabeled data using the object detection network, select a sample image from the candidate set using a policy network, generate a labeled sample based on the selected sample image and the annotation data, wherein the labeled sample includes labels for a plurality of object instances in the sample image, and perform additional training on the object detection network based at least in part on the labeled sample.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.