Method of training image deep learning model and device thereof
US11720790B2 · kind B2 · utility
Assignees
Inventors
Key dates
| Filing date | May 21, 2020 |
| Grant date | Aug 8, 2023 |
| Priority date | — |
| Expiry date | Apr 20, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V10/774
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Disclosed herein is an image deep learning model training method. The method includes sampling a twin negative comprising a first negative sample and a second negative sample by selecting the first negative sample with a highest similarity out of an anchor sample and a positive sample constituting a matching pair in each class and by selecting the second negative sample with a highest similarity to the first negative sample, and training the samples to minimize a loss of a loss function in each class by utilizing the anchor sample, the positive sample, the first and second negative samples for each class. The first negative sample is selected in a different class from a class comprising the matching pair, and the second negative sample is selected in a different class from classes comprising the matching pair and the first negative sample.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.