公开(公告)号：US11579534B2

公开(公告)日：2023-02-14

申请号：US17436113

申请日：2020-02-06

Applicant: ASML NETHERLANDS B.V.

Inventor： Maialen Larranaga ,  Dimitra Gkorou ,  Faegheh Hasibi ,  Alexander Ypma

IPC: G03F7/20 ,  G06N20/00

Abstract: A method of extracting a feature from a data set includes iteratively extracting a feature from a data set based on a visualization of a residual pattern within the data set, wherein the feature is distinct from a feature extracted in a previous iteration, and the visualization of the residual pattern uses the feature extracted in the previous iteration. Visualizing the data set using the feature extracted in the previous iteration may include showing residual patterns of attribute data that are relevant to target data. Visualizing the data set using the feature extracted in the previous iteration may involve adding cluster constraints to the data set, based on the feature extracted in the previous iteration. Additionally or alternatively, visualizing the data set using the feature extracted in the previous iteration may involve defining conditional probabilities conditioned on the feature extracted in the previous iteration.

公开(公告)号：US12254392B2

公开(公告)日：2025-03-18

申请号：US17423658

申请日：2019-12-12

Applicant: ASML NETHERLANDS B.V.

Inventor： Faegheh Hasibi ,  Leon Paul Van Dijk ,  Maialen Larranaga ,  Alexander Ypma ,  Richard Johannes Franciscus Van Haren

IPC: G06F30/398 ,  G03F7/00 ,  G06F30/27 ,  G06N3/04 ,  G06F119/18 ,  G06N3/0464

Abstract: A method for predicting a property associated with a product unit. The method may include: obtaining a plurality of data sets, wherein each of the plurality of data sets includes data associated with a spatial distribution of a parameter across the product unit; representing each of the plurality of data sets as a multidimensional object; obtaining a convolutional neural network model trained with previously obtained multidimensional objects and properties of previous product units; and applying the convolutional neural network model to the plurality of multidimensional objects representing the plurality of data sets, to predict the property associated with the product unit.