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公开(公告)号：US11205119B2
公开(公告)日：2021-12-21
申请号：US15384058
申请日：2016-12-19
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 examining a semiconductor specimen. The method comprises: upon obtaining 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 ground truth data specific for the given application; and obtaining examination-related data specific for the given application and characterizing at least one of the processed one or more FP images. The examination-related application can be, for example, classifying at least one defect presented by at least one FP image, segmenting the at least one FP image, detecting defects in the specimen presented by the at least one FP image, registering between at least two FP images, regression application enabling reconstructing the at least one FP image in correspondence with different examination modality, etc.
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公开(公告)号：US11010665B2
公开(公告)日：2021-05-18
申请号：US15668623
申请日：2017-08-03
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 segmentation a fabrication process (FP) image obtained in a fabrication of a semiconductor specimen. The method comprises: upon obtaining a Deep Neural Network (DNN) trained to provide segmentation-related data, processing a fabrication process (FP) sample using the obtained trained DNN and, resulting from the processing, obtaining by the computer segments-related data characterizing the FP image to be segmented, the obtained segments-related data usable for automated examination of the semiconductor specimen. The DNN is trained using a segmentation training set comprising a plurality of first training samples and ground truth data associated therewith, each first training sample comprises a training image; FP sample comprises the FP image to be segmented.
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公开(公告)号：US10748271B2
公开(公告)日：2020-08-18
申请号：US15962909
申请日：2018-04-25
Applicant: Applied Materials Israel, Ltd.
Inventor： Assaf Asbag , Orly Zvitia , Idan Kaizerman , Efrat Rosenman
Abstract: There are provided system and method of classifying defects in a specimen. The method includes: obtaining one or more defect clusters detected on a defect map of the specimen, each cluster characterized by a set of cluster attributes comprising spatial attributes including spatial density indicative of density of defects in one or more regions accommodating the cluster, each given defect cluster being detected at least based on the spatial density thereof meeting a criterion; for each cluster, applying a cluster classifier to a respective set of cluster attributes thereof to associate the cluster with one or more labels of a predefined set of labels, wherein the cluster classifier is trained using cluster training data; and identifying DOI in each cluster by performing a defect filtration for each cluster using one or more filtering parameters specified in accordance with the label of the cluster.
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公开(公告)号：US20190012781A1
公开(公告)日：2019-01-10
申请号：US16102112
申请日：2018-08-13
Applicant: Applied Materials Israel Ltd.
Inventor： Saar Shabtay , Idan Kaizerman , Amir Watchs
Abstract: Data indicative of a group of defect candidates may be obtained. The data may be indicative of a group of defect candidates and may include values of attributes for each defect candidate of the group of defect candidates. Sub-groups of defect candidates may be iteratively selected for review using a review recipe to classify the defect candidates in each selected sub-group based on the values of attributes of respective defect candidates and classification results of previously reviewed defect candidates. The sub-groups may be selected until a sampling stop condition is fulfilled to obtain a classification output for the wafer. Instructions specifying at least one of the sampling stop condition, the inspection recipe, or the review recipe may be altered and additional defect candidates in a next wafer may be classified by using the altered instructions.
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公开(公告)号：US09715724B2
公开(公告)日：2017-07-25
申请号：US14446295
申请日：2014-07-29
Applicant: Applied Materials Israel Ltd.
Inventor： Ishai Schwarzband , Yan Ivanchenko , Daniel Ravid , Orly Zvitia , Idan Kaizerman
CPC classification number: G06T7/001 , G06K9/4604 , G06K9/6211 , G06K2209/19 , G06K2209/403 , G06T2207/10028 , G06T2207/10061 , G06T2207/30148
Abstract: A method for image processing includes providing a microscopic image of a structure fabricated on a substrate and computer-aided design (CAD) data used in fabricating the structure. The microscopic image is processed by a computer so as to generate a first directionality map, which includes, for a matrix of points in the microscopic image, respective directionality vectors corresponding to magnitudes and directions of edges at the points irrespective of a sign of the magnitudes. The CAD data are processed by the computer so as to produce a simulated image based on the CAD data and to generate a second directionality map based on the simulated image. The first and second directionality maps are compared by the computer so as to register the microscopic image with the CAD data.
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Patent Agency Ranking
公开(公告)号：US11526979B2
公开(公告)日：2022-12-13
申请号：US16993869
申请日：2020-08-14
Applicant: Applied Materials Israel, Ltd.
Inventor： Assaf Asbag , Orly Zvitia , Idan Kaizerman , Efrat Rosenman
Abstract: There are provided system and method of classifying defects in a specimen. The method includes: obtaining one or more defect clusters detected on a defect map of the specimen, each cluster characterized by a set of cluster attributes comprising spatial attributes including spatial density indicative of density of defects in one or more regions accommodating the cluster, each given defect cluster being detected at least based on the spatial density thereof meeting a criterion. The defect map also comprises non-clustered defects. Defects of interest (DOI) are identified in each cluster by performing respective defect filtrations for each cluster and non-clustered defects.
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7.发明授权公开(公告)号：US10803575B2
公开(公告)日：2020-10-13
申请号：US16518589
申请日：2019-07-22
Applicant: APPLIED MATERIALS ISRAEL LTD.
Inventor： Ohad Shaubi , Assaf Asbag , Idan Kaizerman
Abstract: There is provided a system that includes a review tool configured to review at least part of potential defects of an examined object, and assign each of the at least part of the potential defects with a multiplicity of attribute values. The system also includes a computer-based classifier configured to classify, based on the attribute values as assigned, the at least part of potential defects into a set of classes, the set comprising at least a first major class, a second major class and a first minor class, the classifier trained based on a training set comprising a multiplicity of training defects with assigned attribute values, the training defects classified into the set of classes.
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公开(公告)号：US10312161B2
公开(公告)日：2019-06-04
申请号：US14666183
申请日：2015-03-23
Applicant: Applied Materials Israel Ltd.
Inventor： Idan Kaizerman , Yotam Sofer
Abstract: A method for process analysis includes acquiring first inspection data, using a first inspection modality, with respect to a substrate having multiple instances of a predefined pattern of features formed thereon using different, respective sets of process parameters. Characteristics of defects identified in the first inspection data are processed so as to select a first set of defect locations in which the first inspection data are indicative of an influence of the process parameters on the defects. Second inspection data are acquired, using a second inspection modality having a finer resolution than the first inspection modality, of the substrate at the locations in the first set. The defects appearing in the second inspection data are analyzed so as to select, from within the first set of the locations, a second set of the locations in which the second inspection data are indicative of an optimal range of the process parameters.
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公开(公告)号：US20190121331A1
公开(公告)日：2019-04-25
申请号：US16174070
申请日：2018-10-29
Applicant: Applied Materials Israel Ltd.
Inventor： Gadi Greenberg , Idan Kaizerman , Zeev Zohar
IPC: G05B19/418 , H01J37/00 , G06T7/00
Abstract: Inspection apparatus includes an imaging module, which is configured to capture images of defects at different, respective locations on a sample. A processor is coupled to process the images so as to automatically assign respective classifications to the defects, and to autonomously control the imaging module to continue capturing the images responsively to the assigned classifications.
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公开(公告)号：US10049441B2
公开(公告)日：2018-08-14
申请号：US15019894
申请日：2016-02-09
Applicant: Applied Materials Israel Ltd.
Inventor： Saar Shabtay , Idan Kaizerman , Amir Wachs
Abstract: A method for classifying defects of a wafer, the method is executed by a computerized system, the method may include obtaining defect candidate information about a group of defect candidates, wherein the defect candidate information comprises values of attributes per each defect candidate of the group; selecting, by a processor of the computerized system, a selected sub-group of defect candidates in response to values of attributes of defect candidates that belong to at least the selected sub-group; classifying defect candidates of the selected sub-group to provide selected sub-group classification results; repeating, until fulfilling a stop condition: selecting an additional selected sub-group of defect candidates in response to (a) values of attributes of defect candidates that belong to at least the additional selected sub-group; and (b) classification results obtained from classifying at least one other selected sub-group; and classifying defect candidates of the additional selected sub-group to provide additional selected sub-group classification results.
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