Techniques to reconstruct data from acoustically constructed images using machine learning
US12153132B2 · kind B2 · utility
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18Claims
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Key dates
| Filing date | Sep 13, 2021 |
| Grant date | Nov 26, 2024 |
| Priority date | — |
| Expiry date | May 14, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldMeasurement
- WIPO sectorInstruments
Abstract
Acoustic data, such as a full matrix capture (FMC) matrix, can be reconstructed by applying a previously trained decoder machine learning model to one or more encoded acoustic images, such as the TFM image(s), to generate reconstructed acoustic data. A processor can use the reconstructed acoustic data, such as an FMC matrix, to recreate new encoded acoustic images, such as TFM image(s), using different generation parameters (e.g., acoustic velocity, part thickness, acoustic mode, etc.).
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.