Generating refined object proposals using deep-learning models
US10496895B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 22, 2017 |
| Grant date | Dec 3, 2019 |
| Priority date | — |
| Expiry date | Jun 6, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V40/20
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In one embodiment a plurality of patches of an image are processed, using a first set of layers of a convolutional neural network, to output a plurality of object proposals associated with the plurality of patches of the image. Each patch includes one or more pixels of the image. Each object proposal includes a prediction as to a location of an object in the respective patch. Using a second set of layers of the convolutional neural network, the plurality of object proposals outputted by the first set of layers are processed to generate a plurality of refined object proposals. Each refined object proposal includes pixel-level information for the respective patch of the image. The first layer in the second set of layers of the convolutional neural network takes as input the plurality of object proposals outputted by the first set of layers. Each layer after the first layer in the second set of layers takes as input the output of a preceding layer in the second set of layers combined with the output of a respective layer of the first set of layers.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.