Probabilistic loss function for training network with triplets
US10592732B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 21, 2018 |
| Grant date | Mar 17, 2020 |
| Priority date | — |
| Expiry date | Feb 21, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30201
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Some embodiments provide a method for training a machine-trained (MT) network that processes images using multiple network parameters. The method propagates a triplet of input images through the MT network to generate an output value for each of the input images. The triplet includes an anchor first image, a second image of a same category as the anchor image, and a third image of a different category as the anchor image. The method calculates a value of a loss function for the triplet that is based on a probabilistic classification of an output value for the anchor image compared to output values for the second and third images. The method uses the calculated loss function value to train the network parameters.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.