Dynamic self-learning system
US10474928B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 14, 2017 |
| Grant date | Nov 12, 2019 |
| Priority date | — |
| Expiry date | Mar 6, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30242
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In an example, a computerized neural fabric is created by representing each pattern of learned weights of one or more machine learning algorithm-trained models specifying a specific set of products as a column in the computerized neural fabric, each pattern comprising one or more clusters representing combinations of convolutional filters, each cluster learning low level features and sending output via a vertical flow up the corresponding column to a final classification within the corresponding pattern. One or more potential lateral flows between patterns in the computerized neural fabrics is dynamically determined based on resemblance of a new product in a candidate image to the specific sets of products in each of the patterns and identifying possible mutations of the patterns based on the resemblance. Then, one of the one or more potential lateral flows is selected as a new model.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.