Utilizing a deep neural network-based model to identify visually similar digital images based on user-selected visual attributes
US10628708B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 18, 2018 |
| Grant date | Apr 21, 2020 |
| Priority date | — |
| Expiry date | Aug 13, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present disclosure relates to systems, methods, and non-transitory computer readable media for utilizing a deep neural network-based model to identify similar digital images for query digital images. For example, the disclosed systems utilize a deep neural network-based model to analyze query digital images to generate deep neural network-based representations of the query digital images. In addition, the disclosed systems can generate results of visually-similar digital images for the query digital images based on comparing the deep neural network-based representations with representations of candidate digital images. Furthermore, the disclosed systems can identify visually similar digital images based on user-defined attributes and image masks to emphasize specific attributes or portions of query digital images.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.