Training method for robust neural network based on feature matching
US11682194B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 22, 2022 |
| Grant date | Jun 20, 2023 |
| Priority date | — |
| Expiry date | Sep 22, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V20/70
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A training method for a robust neural network based on feature matching is provided in this disclosure, which includes following steps. Step A, a first stage model is initialized. The first stage model includes a backbone network, a feature matching module and a fullple loss function. Step B, the first stage model is trained by using original training data to obtain a second stage model. Step C, the second stage model is attacked so as to generate PGD adversarial samples of the original training data, and the second stage model is trained again with the generated adversarial samples and the original training data. Step D, training parameters are adjusted and the second stage model is trained again, and parameters for which the model has highest accuracy on an original test set are saved.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.