Deep learning for semantic segmentation of pattern
US11847570B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 10, 2022 |
| Grant date | Dec 19, 2023 |
| Priority date | — |
| Expiry date | Jun 10, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30148
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method for training a deep learning model of a patterning process. The method includes obtaining (i) training data comprising an input image of at least a part of a substrate having a plurality of features and a truth image, (ii) a set of classes, each class corresponding to a feature of the plurality of features of the substrate within the input image, and (iii) a deep learning model configured to receive the training data and the set of classes, generating a predicted image, by modeling and/or simulation of the deep learning model using the input image, assigning a class of the set of classes to a feature within the predicted image based on matching of the feature with a corresponding feature within the truth image, and generating, by modeling and/or simulation, a trained deep learning model by iteratively assigning weights using a loss function.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.