Attribution and generation of saliency visualizations for machine-learning models
US11755948B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 18, 2019 |
| Grant date | Sep 12, 2023 |
| Priority date | — |
| Expiry date | Apr 1, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/10
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods, systems, devices, and tangible non-transitory computer readable media for saliency visualization are provided. The disclosed technology can include receiving a data input including a plurality of features. The data input can be segmented into regions. At least one of the regions can include two or more of the features. Attribution scores can be respectively generated for features of the data input. The attribution scores for each feature can be indicative of a respective saliency of such feature. A respective gain value for each region can be determined over one or more iterations based on the respective attribution scores associated with the features included in the region. Further, at each iteration one or more of the regions with the greatest gain values can be added to a saliency mask. Furthermore, at each iteration a saliency visualization can be produced based on the saliency mask.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.