公开(公告)号：US11562476B2

公开(公告)日：2023-01-24

申请号：US17011949

申请日：2020-09-03

Applicant: Applied Materials Israel Ltd.

Inventor： Irad Peleg

IPC: G06T7/00 ,  G06N20/00

Abstract: There is provided a system to examine a semiconductor specimen, the system comprising a processor and memory circuitry configured to obtain a training sample comprising an image of a semiconductor specimen and a design image based on design data, train a machine learning module, wherein the training includes minimizing a function representative of a difference between a simulated image generated by the machine learning module based on a given design image, and a corrected image corresponding to a given image after correction of pixel position of the given image in accordance with a given displacement matrix, wherein the minimizing includes optimizing parameters of the machine learning module and of the given displacement matrix, wherein the trained machine learning module is usable to generate a simulated image of a specimen based on a design image of the specimen.

公开(公告)号：US12131458B2

公开(公告)日：2024-10-29

申请号：US18076324

申请日：2022-12-06

Applicant: Applied Materials Israel Ltd.

Inventor： Irad Peleg

IPC: G06T7/00 ,  G06N20/00

CPC classification number: G06T7/0006 ,  G06N20/00 ,  G06T7/001 ,  G06T2207/20081 ,  G06T2207/30148

Abstract: There is provided a system to examine a semiconductor specimen, the system comprising a processor and memory circuitry configured to obtain a training sample comprising an image of a semiconductor specimen and a design image based on design data, train a machine learning module, wherein the training includes minimizing a function representative of a difference between a simulated image generated by the machine learning module based on a given design image, and a corrected image corresponding to a given image after correction of pixel position of the given image in accordance with a given displacement matrix, wherein the minimizing includes optimizing parameters of the machine learning module and of the given displacement matrix, wherein the trained machine learning module is usable to generate a simulated image of a specimen based on a design image of the specimen.

公开(公告)号：US11379972B2

公开(公告)日：2022-07-05

申请号：US16892139

申请日：2020-06-03

Applicant: Applied Materials Israel Ltd.

Inventor： Irad Peleg ,  Ran Schleyen ,  Boaz Cohen

IPC: G06T7/00 ,  G01N21/95 ,  G06T7/11 ,  G06N3/06 ,  G06K9/62 ,  G06V10/75

Abstract: A system of classifying a pattern of interest (POI) on a semiconductor specimen, where the system includes a processor and memory circuitry configured to obtain a high-resolution image of the POI, and generate data usable for classifying the POI in accordance with a defectiveness-related classification. Generating the data utilizes a machine learning model that has been trained in accordance with training samples. The training samples include a high-resolution training image captured by scanning a respective training pattern on a specimen, the respective training pattern being similar to the POI, and a label associated with the image. The label is derivative of low-resolution inspection of the respective training pattern.

公开(公告)号：US11790515B2

公开(公告)日：2023-10-17

申请号：US17751507

申请日：2022-05-23

Applicant: Applied Materials Israel Ltd.

Inventor： Irad Peleg ,  Ran Schleyen ,  Boaz Cohen

IPC: G06T7/00 ,  G06T7/11 ,  G06F18/22 ,  G06F18/214 ,  G06V10/82 ,  G06V10/44 ,  G06V20/69 ,  G01N21/95 ,  G06N3/06

CPC classification number: G06T7/0004 ,  G01N21/9501 ,  G06F18/214 ,  G06F18/22 ,  G06N3/06 ,  G06T7/0008 ,  G06T7/11 ,  G06V10/454 ,  G06V10/82 ,  G06V20/69 ,  G06T2207/10061 ,  G06T2207/20084 ,  G06T2207/30148

Abstract: A system for classifying a pattern of interest (POI) on a semiconductor specimen is disclosed. The system comprises a processor and memory circuitry. The memory circuitry is configured to obtain a high-resolution image of the POI, and to generate data usable for classifying the POI in accordance with a defectiveness-related classification. To generate the data, a machine learning model is utilized that has been trained in accordance with training samples. The training samples include a high-resolution training image captured by scanning a respective training pattern on a specimen, the respective training pattern being similar to the POI. The training samples also include a label associated with the image, the label being derivative of low-resolution inspection of the respective training pattern.

公开(公告)号：US11449711B2

公开(公告)日：2022-09-20

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: G06T7/00 ,  G06K9/62

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.