Generating object proposals using deep-learning models
US10255522B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 15, 2017 |
| Grant date | Apr 9, 2019 |
| Priority date | — |
| Expiry date | Jun 29, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V20/64
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In one embodiment, a plurality of patches of an image are processed using a first deep-learning model to detect a plurality of features associated with the first patch of the image. Each patch includes one or more pixels of the image. Using a second deep-learning model, a respective object proposal is generated for each of the plurality of patches of the image. The second deep-learning model takes as input the plurality of detected features associated with the respective patch of the image, and each object proposal includes a prediction as to a location of an object in the patch. Using a third deep-learning model, a respective score is computed for each object proposal generated using the second deep-learning model. The third deep-learning model takes as input the plurality of detected features associated with the respective patch of the image, and the object score may include a likelihood that the patch contains an entire object.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.