System and method for unsupervised domain adaptation with mixup training
US11537901B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 31, 2019 |
| Grant date | Dec 27, 2022 |
| Priority date | — |
| Expiry date | Mar 17, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/044
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A system and method for domain adaptation involves a first domain and a second domain. A machine learning system is trained with first sensor data and first label data of the first domain. Second sensor data of a second domain is obtained. Second label data is generated via the machine learning system based on the second sensor data. Inter-domain sensor data is generated by interpolating the first sensor data of the first domain with respect to the second sensor data of the second domain. Inter-domain label data is generated by interpolating first label data of the first domain with respect to second label data of the second domain. The machine learning system is operable to generate inter-domain output data in response to the inter-domain sensor data. Inter-domain loss data is generated based on the inter-domain output data with respect to the inter-domain label data. Parameters of the machine learning system are updated upon optimizing final loss data that includes at least the inter-domain loss data. After domain adaptation, the machine learning system, which is operable in the first domain, is adapted to generate current label data that identifies current sensor data of the sec…
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.