Domain adaption learning system
US11620527B2 · kind B2 · utility
1Cited by
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17Claims
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Key dates
| Filing date | Jan 30, 2019 |
| Grant date | Apr 4, 2023 |
| Priority date | — |
| Expiry date | Jan 8, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Described is a system for adapting a deep convolutional neural network (CNN). A deep CNN is first trained on an annotated source image domain. The deep CNN is adapted to a new target image domain without requiring new annotations by determining domain agnostic features that map from the annotated source image domain and a target image domain to a joint latent space, and using the domain agnostic features to map the joint latent space to annotations for the target image domain.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.