Systems and methods for multi-teacher group-distillation for long-tail classification
US12394182B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 21, 2022 |
| Grant date | Aug 19, 2025 |
| Priority date | — |
| Expiry date | Dec 13, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V20/582
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods and systems for classifying a long-tail distribution of data. Data deriving from one or more sensors is classified into a plurality of classes by using (i) a feature-extractor backbone model configured to extract features from the data, and (ii) a classifier model configured to classify the data based on the extracted features. The plurality of classes are grouped, with each group assigned to a respective teacher model. Each respective teacher model is trained with the data in its respective group, as well as the feature-extractor backbone model. The outputs of the teacher models are then merged into a final class prediction model configured to classify the data.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.