Invention Grant
- Patent Title: Deep learning for semantic segmentation of pattern
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Application No.: US16968966Application Date: 2019-02-15
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Publication No.: US11379970B2Publication Date: 2022-07-05
- Inventor: Adrianus Cornelis Matheus Koopman , Scott Anderson Middlebrooks , Antoine Gaston Marie Kiers , Mark John Maslow
- Applicant: ASML NETHERLANDS B.V.
- Applicant Address: NL Veldhoven
- Assignee: ASML NETHERLANDS B.V.
- Current Assignee: ASML NETHERLANDS B.V.
- Current Assignee Address: NL Veldhoven
- Agency: Pillsbury Winthrop Shaw Pittman LLP
- International Application: PCT/EP2019/053803 WO 20190215
- International Announcement: WO2019/162204 WO 20190829
- Main IPC: G06T7/00
- IPC: G06T7/00 ; G06T7/11 ; G03F7/20 ; G06K9/62 ; G06N3/08

Abstract:
A method for training a deep learning model of a patterning process. The method includes obtaining (i) training data including an input image of at least a part of a substrate having a plurality of features and including 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 with 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.
Public/Granted literature
- US20210374936A1 DEEP LEARNING FOR SEMANTIC SEGMENTATION OF PATTERN Public/Granted day:2021-12-02
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