Encoding of training data for training of a neural network
US12374098B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 17, 2023 |
| Grant date | Jul 29, 2025 |
| Priority date | — |
| Expiry date | Mar 21, 2044 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V10/774
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method for encoding training data for training of a neural network comprises: obtaining training data including multiple datasets, each dataset comprises images annotated with at least one respective object class, forming, each dataset having an individual background class associated with the object class; encoding the images of the datasets to be associated with their respective individual background class; encoding image patches belonging to annotated object classes to be associated with their respective object class; encoding each of the datasets, to include an ignore attribute (“ignore”) to object classes that are annotated only in the other datasets and to background classes formed for the other datasets of the multiple datasets, the ignore attribute indicating that the assigned object class and background classes do not contribute in adapting the neural network in training using the respective dataset; and providing the encoded training data for training of a neural network.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.