System and method of machine learning using embedding networks
US12086719B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 9, 2020 |
| Grant date | Sep 10, 2024 |
| Priority date | — |
| Expiry date | May 9, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V10/82
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods of generating interpretive data associated with data sets. Embodiments of systems may be for adapting Grad-CAM methods for embedding networks. The system includes a processor and a memory. The memory stores processor-executable instructions that, when executed, configure the processor to: obtain a subject data set; generate a feature embedding based on the subject data set; determine an embedding gradient weight based on a prior-trained embedding network and the feature embedding associated with the subject data set, the prior-trained embedding network defined based on a plurality of embedding gradient weights respectively corresponding to a feature map generated based on a plurality of training samples, and wherein the embedding gradient weight is determined based on querying a feature space for the feature embedding associated with the subject data set; and generate signals for communicating interpretive data associated with the embedding gradient weight.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.