Using image pre-processing to generate a machine learning model
US11087173B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 27, 2018 |
| Grant date | Aug 10, 2021 |
| Priority date | — |
| Expiry date | Dec 27, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30256
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and processes can reduce an amount of training data used to generate a machine learning model while maintaining or improving a resultant of the machine learning model. The amount of training data may be reduced by pre-processing the training data to normalize the training data. The training data may include images of portions of an elongated object, such as a road. Each of the images can be normalized by, for example, rotating each of the images such that the depicted roads are horizontal or otherwise share the same angle. By aligning disparate images of roads, it is possible to reduce the amount of training data and to increase the accuracy of the machine learning model. Further, the use of normalized images by the machine learning model enables a reduction in computing resources used to apply data to the machine learning model to, for example, identify lane markings within images.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.