Machine learning model with layer level uncertainty metrics
US11809976B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 27, 2023 |
| Grant date | Nov 7, 2023 |
| Priority date | — |
| Expiry date | Jan 27, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/082
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods are disclosed for classifying objects by a machine learning (ML) model. The ML model includes one or more layer level classification models to generate classifications and uncertainty metrics in the classifications and a meta-model to generate a final classification and confidence based on the underlying classifications and uncertainty metrics. In some implementations, the ML model provides an object to be classified to one or more layer level classification models, and the layer level classification models generate a classification for the object and an uncertainty metric in the classification. The meta-model receives the classifications and uncertainty metrics from the one or more layer level classification models and generates the final classification and confidence in the final classification. The uncertainty metrics may also be output by the ML model or used to adjust the meta-model to improve the final classification and confidence.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.