Network reparameterization for new class categorization
US11087184B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 24, 2019 |
| Grant date | Aug 10, 2021 |
| Priority date | — |
| Expiry date | Feb 5, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/048
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A computer-implemented method and system are provided for training a model for New Class Categorization (NCC) of a test image. The method includes decoupling, by a hardware processor, a feature extraction part from a classifier part of a deep classification model by reparametrizing learnable weight variables of the classifier part as a combination of learnable variables of the feature extraction part and of a classification weight generator of the classifier part. The method further includes training, by the hardware processor, the deep classification model to obtain a trained deep classification model by (i) learning the feature extraction part as a multiclass classification task, and (ii) episodically training the classifier part by learning a classification weight generator which outputs classification weights given a training image.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.