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公开(公告)号：US20210343000A1
公开(公告)日：2021-11-04
申请号：US16866463
申请日：2020-05-04
Applicant: Applied Materials Israel Ltd.
Inventor： Ran SCHLEYEN , Eyal ZAKKAY , Boaz COHEN
IPC: G06T7/00
Abstract: There is provided a system comprising a processor configured to obtain a set of images of a semiconductor specimen, (1) for an image of the set of images, select at least one algorithmic module MS out of a plurality of algorithmic modules, (2) feed the image to MS to obtain data DMS representative of one or more defects in the image, (3) obtain a supervised feedback regarding rightness of data DMS, (4) repeat (1) to (3) for a next image until a completion criterion is met, wherein an algorithmic module selected at (1) is different for at least two different images of the set of images, generate, based on the supervised feedback, a score for each of a plurality of the algorithmic modules, and use scores to identify one or more algorithmic modules Mbest as the most adapted for providing data representative of one or more defects in the set of images.
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公开(公告)号：US20210383530A1
公开(公告)日：2021-12-09
申请号：US16892139
申请日：2020-06-03
Applicant: Applied Materials Israel Ltd.
Inventor： Irad PELEG , Ran SCHLEYEN , Boaz COHEN
Abstract: A system of classifying a pattern of interest (POI) on a semiconductor specimen, the system comprising 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, wherein the generating utilizes a machine learning model that has been trained in accordance with training samples comprising: 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 being derivative of low-resolution inspection of the respective training pattern.
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公开(公告)号：US20220301151A1
公开(公告)日：2022-09-22
申请号：US17751507
申请日：2022-05-23
Applicant: Applied Materials Israel Ltd.
Inventor： Irad PELEG , Ran SCHLEYEN , Boaz Cohen
Abstract: A system of classifying a pattern of interest (POI) on a semiconductor specimen, the system comprising 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, wherein the generating utilizes a machine learning model that has been trained in accordance with training samples comprising: 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 being derivative of low-resolution inspection of the respective training pattern.
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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
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.
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