公开(公告)号：US20220222806A1

公开(公告)日：2022-07-14

申请号：US17605217

申请日：2020-03-24

Applicant: APPLIED MATERIALS ISRAEL LTD.

Inventor： Ohad SHAUBI ,  Boaz COHEN ,  Kirill SAVCHENKO ,  Ore SHTALRID

IPC: G06T7/00 ,  G06V10/764 ,  G06V10/774 ,  G06V10/776

Abstract: There is provided a method of automated defects' classification, and a system thereof. The method comprises obtaining data informative of a set of defects' physical attributes usable to distinguish between defects of different classes among the plurality of classes; training a first machine learning model to generate, for the given defect, a multi-label output vector informative of values of the physical attributes, thereby generating for the given defect a multi-label descriptor; and using the trained first machine learning model to generate multi-label descriptors of the defects in the specimen. The method can further comprise obtaining data informative of multi-label data sets, each data set being uniquely indicative of a respective class of the plurality of classes and comprising a unique set of values of the physical attributes; and classifying defects in the specimen by matching respectively generated multi-label descriptors of the defects to the multi-label data sets.

公开(公告)号：US20210209418A1

公开(公告)日：2021-07-08

申请号：US16733219

申请日：2020-01-02

Applicant: Applied Materials Israel Ltd.

Inventor： Ran BADANES ,  Ran SCHLEYEN ,  Boaz COHEN ,  Irad PELEG ,  Denis SUHANOV ,  Ore SHTALRID

IPC: G06K9/62 ,  G06T7/00

Abstract: There is provided a method of defect detection on a specimen and a system thereof. The method includes: obtaining a runtime image representative of at least a portion of the specimen; processing the runtime image using a supervised model to obtain a first output indicative of the estimated presence of first defects on the runtime image; processing the runtime image using an unsupervised model component to obtain a second output indicative of the estimated presence of second defects on the runtime image; and combining the first output and the second output using one or more optimized parameters to obtain a defect detection result of the specimen.