Neural networks for object detection
US10013773B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 16, 2016 |
| Grant date | Jul 3, 2018 |
| Priority date | — |
| Expiry date | Jan 2, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A neural network system for identifying positions of objects in an input image can include an object detector neural network, a memory interface subsystem, and an external memory. The object detector neural network is configured to, at each time step of multiple successive time steps, (i) receive a first neural network input that represents the input image and a second neural network input that identifies a first set of positions of the input image that have each been classified as showing a respective object of the set of objects, and (ii) process the first and second inputs to generate a set of output scores that each represents a respective likelihood that an object that is not one of the objects shown at any of the positions in the first set of positions is shown at a respective position of the input image that corresponds to the output score.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.