Machine learning via a two-dimensional symbol
US10331967B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 5, 2018 |
| Grant date | Jun 25, 2019 |
| Priority date | — |
| Expiry date | Dec 5, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V30/43
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods of facilitating machine learning via a 2-D symbol are disclosed. Features of an object are received in a first computing system having a 2-D symbol creation application module installed thereon. A multi-layer 2-D symbol is formed from the features according to a set of symbol creation rules. 2-D symbol is a matrix of N×N pixels partitioned into a number of sub-matrices with each sub-matrix containing one feature, where N is a positive integer. Meaning of the combined features in the 2-D symbol is learned in a second computing system by using an image processing technique to classify the 2-D symbol transmitted from the first computing system. The symbol creation rules determine the importance order, size and location of sub-matrices in the 2-D symbol.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.