Techniques for extracting associations between text labels and symbols and links in schematic diagrams
US12288411B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 6, 2022 |
| Grant date | Apr 29, 2025 |
| Priority date | — |
| Expiry date | Sep 21, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V30/422
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In example embodiments, techniques are provided that use two different ML models (a symbol association ML model and a link association ML model), one to extract associations between text labels and one to extract associations between symbols and links, in a schematic diagram (e.g., P&ID) in an image-only format. The two models may use different ML architectures. For example, the symbol association ML model may use a deep learning neural network architecture that receives for each possible text label and symbol pair both a context and a request, and produces a score indicating confidence the pair is associated. The link association ML model may use a gradient boosting tree architecture that receives for each possible text label and link pair a set of multiple features describing at least the geometric relationship between the possible text label and link pair and produces a score indicating confidence the pair is associated.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.