Method for characterising samples using neural networks
US11828652B2 · kind B2 · utility
Assignees
Inventors
Key dates
| Filing date | Nov 30, 2018 |
| Grant date | Nov 28, 2023 |
| Priority date | — |
| Expiry date | Aug 29, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30188
- WIPO fieldMeasurement
- WIPO sectorInstruments
Abstract
A method for characterizing a sample using spectral images of the sample. At least one volume of values of an observed parameter is generated from the images for a plurality of coordinates of the pixels of the images and a plurality of acquisitions. At least one set of input data from the volume is extracted, with the input data corresponding to the values of the parameter, for a pixel of given coordinates in various acquisitions, to which values at least one conversion function has been applied. The at least one neural network is trained using the input data in order to extract therefrom at least one feature of the sample to be characterized. The at least one feature extracted by the neural network is used to perform a classification of the input data into a plurality of classes, each class being representative of at least one feature of the sample.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.