Method for neural network training using differences between a plurality of images, and apparatus using the method
US10643107B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 13, 2019 |
| Grant date | May 5, 2020 |
| Priority date | — |
| Expiry date | Nov 13, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V2201/03
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present disclosure provides a method for training a neural network that extracts a feature of an image by using data related to a difference between image, and an apparatus using the same. A neural network training method performed by a computing device according to an exemplary embodiment of the present disclosure includes: acquiring a reference image photographed with a first setting with respect to an object and a first comparison image photographed with a second setting with respect to the object; acquiring feature data of the reference image from a first neural network trained by using the reference image; acquiring feature data of a first extract image from a second neural network, wherein the second neural network is trained by using the first extract image formed from data related to a difference between the reference image and the first comparison image; and training a third neural network by using the feature data of the reference image and the feature data of the first extracted image.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.