Machine learning techniques for differentiability scoring of digital images
US11748451B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 15, 2020 |
| Grant date | Sep 5, 2023 |
| Priority date | — |
| Expiry date | Jun 16, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An image differentiation system receives input feature vectors for multiple input images and reference feature vectors for multiple reference images. In some cases, the feature vectors are extracted by an image feature extraction module trained based on training image triplets. A differentiability scoring module determines a differentiability score for each input image based on a distance between the input feature vectors and the reference feature vectors. The distance for each reference feature vector is modified by a weighting factor based on interaction metrics associated with the corresponding reference image. In some cases, an input image is identified as a differentiated image based on the corresponding differentiability score. Additionally or alternatively, an image modification module determines an image modification that increases the differentiability score of the input image. The image modification module generates a recommended image by applying the image modification to the input image.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.