Method for classification of unique/rare cases by reinforcement learning in neural networks
US10776664B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 15, 2017 |
| Grant date | Sep 15, 2020 |
| Priority date | — |
| Expiry date | Mar 16, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V20/56
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Some embodiments are directed to a method to reinforce deep neural network learning capacity to classify rare cases, which includes the steps of training a first deep neural network used to classify generic cases of original data into specified labels; localizing discriminative class-specific features within the original data processed through the first deep neural network and mapping the discriminative class-specific features as spatial-probabilistic labels; training a second-deep neural network used to classify rare cases of the original data into the spatial-probabilistic labels; and training a combined deep neural network used to classify both generic and rare cases of the original data into primary combined specified and spatial-probabilistic labels.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.