Machine learning platform for performing large scale data analytics
US10902270B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 16, 2016 |
| Grant date | Jan 26, 2021 |
| Priority date | — |
| Expiry date | Feb 16, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V20/54
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
To address problems that video imaging systems and platforms face when analyzing image and video content for detection and feature extraction, a solution is provided in which accumulating significant amounts of data suitable for training and learning analytics is leveraged to improve over time, the classifiers used to perform the detection and feature extraction, by employing a larger search space and generate additional and more complex classifiers through distributed processing. A distributed learning platform is therefore provided, which is configured for operating on large scale data, in a true big data paradigm. The learning platform is operable to empirically estimate a set of optimal feature vectors and a set of discriminant functions using a parallelizable learning algorithm. A method of adding new data into a database utilized by such a learning platform is also provided. The method comprises identifying an unrepresented sample space; determining new data samples associated with the unrepresented sample space; and adding the new data samples to the database.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.