Systems and methods for learning across multiple chemical sensing units using a mutual latent representation
US11106977B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 21, 2020 |
| Grant date | Aug 31, 2021 |
| Priority date | — |
| Expiry date | Feb 21, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/10
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods for training models across multiple sensing units in a chemical sensing system are described. The chemical sensing system comprises at least one computer processor and at least one computer readable medium including instructions that, when executed by the at least one computer processor, cause the chemical sensing system to perform a training process. The training process comprises accessing a training dataset including first values representing first signals output from a first chemical sensing unit of multiple chemical sensing units, and second values representing second signals output from a second chemical sensing unit of the multiple chemical sensing units, and training a set of models to relate the first values and the second values to a mutual latent representation using the training dataset.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.