Ensemble learning based image classification systems
US10387772B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 22, 2018 |
| Grant date | Aug 20, 2019 |
| Priority date | — |
| Expiry date | Oct 22, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F18/259
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An ensemble learning based image classification system contains multiple cellular neural networks (CNN) based integrated circuits (ICs) operatively coupling together as a set of base learners of an ensemble for an image classification task. Each CNN based IC is configured with at least one distinct deep learning model in form of filter coefficients. The ensemble learning based image classification system further contains a controller configured as a meta learner of the ensemble and a memory based data buffer for holding various data used in the ensemble by the controller and the CNN based ICs. Various data may include input imagery data to be classified. Various data may also include extracted feature vectors or image classification outputs out of the set of base learners. The extracted feature vectors or image classification outputs are then used by the meta learner to further perform the image classification task.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.