-
公开(公告)号：US11348224B2
公开(公告)日：2022-05-31
申请号：US16833380
申请日：2020-03-27
Applicant: Applied Materials Israel Ltd.
Inventor： Ariel Shkalim , Vladimir Ovechkin , Evgeny Bal , Ronen Madmon , Ori Petel , Alexander Chereshnya , Oren Shmuel Cohen , Boaz Cohen
Abstract: There is provided a mask inspection system and a method of mask inspection. The method comprises: during a runtime scan of a mask of a semiconductor specimen, processing a plurality of aerial images of the mask acquired by the mask inspection system to calculate a statistic-based Edge Positioning Displacement (EPD) of a potential defect, wherein the statistic-based EPD is calculated using a Print Threshold (PT) characterizing the mask and is applied to each of the one or more acquired aerial images to calculate respective EPD of the potential defect therein; and filtering the potential defect as a “runtime true” defect when the calculated statistic-based EPD exceeds a predefined EPD threshold, and filtering out the potential defect as a “false” defect when the calculated statistic-based EPD is lower than the predefined EPD threshold. The method can further comprise after-runtime EPD-based filtering of the plurality of “runtime true” defects.
-
公开(公告)号：US11199506B2
公开(公告)日：2021-12-14
申请号：US16280869
申请日：2019-02-20
Applicant: Applied Materials Israel Ltd.
Inventor： Ohad Shaubi , Assaf Asbag , Boaz Cohen
Abstract: There is provided a system and method of generating a training set usable for examination of a semiconductor specimen. The method comprises: obtaining a simulation model capable of simulating effect of a physical process on fabrication process (FP) images depending on the values of parameters of the physical process; applying the simulation model to an image to be augmented for the training set and thereby generating one or more augmented images corresponding to one or more different values of the parameters of the physical process; and including the generated one or more augmented images into the training set. The training set can be usable for examination of the specimen using a trained Deep Neural Network, automated defect review, automated defect classification, automated navigation during the examination, automated segmentation of FP images, automated metrology based on FP images and other examination processes that include machine learning.
-
公开(公告)号：US10832092B2
公开(公告)日：2020-11-10
申请号：US16631155
申请日：2019-02-07
Applicant: APPLIED MATERIALS ISRAEL LTD.
Inventor： Ohad Shaubi , Assaf Asbag , Boaz Cohen
Abstract: There is provided a method of examination of a semiconductor specimen. The method comprises: upon obtaining by a computer a Deep Neural Network (DNN) trained for a given examination-related application within a semiconductor fabrication process, processing together one or more fabrication process (FP) images using the obtained trained DNN, wherein the DNN is trained using a training set comprising synthetic images specific for the given application; and obtaining, by the computer, examination-related data specific for the given application, and characterizing at least one of the processed one or more FP images. Generating the training set can comprise: training an auxiliary DNN to generate a latent space, generating a synthetic image by applying the trained auxiliary DNN to a point selected in the generated latent space, and adding the generated synthetic image to the training set.
-
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
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：US11348001B2
公开(公告)日：2022-05-31
申请号：US15675477
申请日：2017-08-11
Applicant: Applied Materials Israel Ltd.
Inventor： Leonid Karlinsky , Boaz Cohen , Idan Kaizerman , Efrat Rosenman , Amit Batikoff , Daniel Ravid , Moshe Rosenweig
Abstract: There are provided system and method of classifying defects in a semiconductor specimen. The method comprises: upon obtaining by a computer a Deep Neural Network (DNN) trained to provide classification-related attributes enabling minimal defect classification error, processing a fabrication process (FP) sample using the obtained trained DNN; and, resulting from the processing, obtaining by the computer classification-related attributes characterizing the at least one defect to be classified, thereby enabling automated classification, in accordance with the obtained classification-related attributes, of the at least one defect presented in the FP image. The DNN is trained using a classification training set comprising a plurality of first training samples and ground truth data associated therewith, each first training sample comprising a training image presenting at least one defect and the ground truth data is informative of classes and/or class distribution of defects presented in the respective first training samples; the FP sample comprises a FP image presenting at least one defect to be classified.
-
Patent Agency Ranking
公开(公告)号：US11151710B1
公开(公告)日：2021-10-19
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.
-
公开(公告)号：US11138507B2
公开(公告)日：2021-10-05
申请号：US15719433
申请日：2017-09-28
Applicant: Applied Materials Israel Ltd.
Inventor： Assaf Asbag , Boaz Cohen
Abstract: A system, method and computer software product, the system capable of classifying defects and comprising: an hardware-based GUI component; and a processing and memory circuitry configured to: a. upon obtaining data informative of a plurality of defects and attribute values thereof, using the attribute values to create initial classification of the plurality of defects into a plurality of classes; b. for a given class, presenting to a user, by the hardware-based GUI component, an image of a defect initially classified to the given class with a low likelihood, wherein the image is presented along with images of one or more defects initially classified to the given class with the highest likelihood; and c. subject to confirming by the user, using the hardware-based GUI component, that the at least one defect is to be classified to the given class, indicating the at least one defect as belonging to the given class.
-
公开(公告)号：US09927375B2
公开(公告)日：2018-03-27
申请号：US14977379
申请日：2015-12-21
Applicant: Applied Materials Israel, Ltd.
Inventor： Shay Attal , Ori Petel , Sergey Latinsky , Sergey Khristo , Boaz Cohen
IPC: G01N21/00 , G01N21/956 , G01N21/88
CPC classification number: G01N21/956 , G01N21/8851 , G01N2021/95676 , G03F1/84
Abstract: According to an embodiment of the invention there may be provided a system for assigning lithographic mask inspection process parameters. The system may include a search module, a decision module and a memory module. The memory module may be configured to store an expected image expected to be formed on a photoresist during a lithographic process that involves illuminating the lithographic mask. The search module may be configured to search in the expected image for printable features. The decision module may be configured to assign a first lithographic mask inspection process parameter to lithographic mask areas related to printable features and assign a second lithographic mask inspection process parameter to at least some lithographic mask areas that are not associated with printable features. The second lithographic mask inspection process parameter may differ from the first lithographic mask inspection process parameter.
-
公开(公告)号：US11940390B2
公开(公告)日：2024-03-26
申请号：US17829593
申请日：2022-06-01
Applicant: Applied Materials Israel Ltd.
Inventor： Yotam Sofer , Shaul Engler , Boaz Cohen , Saar Shabtay , Amir Bar , Marcelo Gabriel Bacher
CPC classification number: G01N21/8851 , G06F18/00 , G06F30/27 , G06V10/70 , G06V10/993 , G06V20/69 , G01N2021/8854
Abstract: A system, method and computer readable medium for examining a specimen, the method comprising: obtaining defects of interest (DOIs) and false alarms (FAs) from a review subset selected from a group of potential defects received from an inspection tool, each potential defect is associated with attribute values defining a location of the potential defect in an attribute space; generating a representative subset of the group, comprising potential defects selected in accordance with a distribution of the potential defects within the attribute space, and indicating the potential defects in the representative subset as FA; and training a classifier using data informative of the attribute values of the DOIs, the potential defects of the representative subset, and respective indications thereof as DOIs or FAs, wherein the trained classifier is to be applied to at least some of the potential defects to obtain an estimation of a number of expected DOIs.
-
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.
-
-
-
-
-
-
-
-
-
Search Results
32
records
(took 0.024 seconds)
