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11.发明授权公开(公告)号：US12183066B2
公开(公告)日：2024-12-31
申请号：US17521499
申请日：2021-11-08
Applicant: Applied Materials Israel Ltd.
Inventor： Leonid Karlinsky , Boaz Cohen , Idan Kaizerman , Efrat Rosenman , Amit Batikoff , Daniel Ravid , Moshe Rosenweig
IPC: G06N3/08 , G06F18/2413 , G06N3/045 , G06V10/44 , G06V10/764 , G06V10/82 , G06V10/98
Abstract: A computerized system and method of training a deep neural network (DNN) is provided. The DNN is trained in a first training cycle using a first training set including first training samples. Each first training sample includes at least one first training image synthetically generated based on design data. Upon receiving a user feedback with respect to the DNN trained using the first training set, a second training cycle is adjusted based on the user feedback by obtaining a second training set including augmented training samples. The DNN is re-trained using the second training set. The augmented training samples are obtained by augmenting at least part of the first training samples using defect-related synthetic data. The trained DNN is usable for examination of a semiconductor specimen.
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公开(公告)号：US10720367B2
公开(公告)日：2020-07-21
申请号：US16429533
申请日：2019-06-03
Applicant: Applied Materials Israel Ltd.
Inventor： Idan Kaizerman , Yotam Sofer
IPC: H01L21/66 , H01J37/28 , H01J37/22 , G03F7/20 , H01J37/317 , H01J37/304
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：US10190991B2
公开(公告)日：2019-01-29
申请号：US15343090
申请日：2016-11-03
Applicant: Applied Materials Israel Ltd.
Inventor： Yotam Sofer , Idan Kaizerman
Abstract: Examining an object, comprising: receiving potential defects, each associated with a location; performing first clustering of the potential defects to obtain first and second subsets, the clustering performed such that potential defects in the first subset are denser in a physical area than potential defects in the second subset; automatically assigning first validity probabilities to potential defects in the first and second subsets; selecting for review potential defects from the first and second subsets, according to a third policy, and in accordance with a strategy for combining top elements and randomly selected elements from the merged list; receiving indications for potential defects in part of the potential defect lists, subsequent to potential defects being reviewed; updating the policies in accordance with validation or classification of items in the first and second subsets; and repeating said assigning, selecting, receiving and updating with the updated policies, until a stopping criteria is observed.
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14.发明授权公开(公告)号：US10161882B1
公开(公告)日：2018-12-25
申请号：US15222824
申请日：2016-07-28
Applicant: Applied Materials Israel Ltd.
Inventor： Idan Kaizerman , Mark Geshel
Abstract: A method, computerized system and computer program product for examining an object using a processor operatively connected to a memory, the method comprising: accommodating in the memory data indicative of a plurality of alignment targets, each alignment target associated with a target location on an object; accommodating in the memory a plurality of locations to be captured; and selecting by the processor an alignment target subset of the plurality of alignment targets, such that each of the plurality of locations is associated with and is within a determined distance from a single alignment target from the alignment target subset, the distance determined in accordance with a provided field of view, and wherein the alignment target subset comprises fewer targets than locations to be reviewed, the alignment target being usable for aligning the object relative to an examination tool for capturing the locations associated with the single alignment target.
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公开(公告)号：US20160163038A1
公开(公告)日：2016-06-09
申请号：US15019894
申请日：2016-02-09
Applicant: Applied Materials Israel Ltd.
Inventor： Saar Shabtay , Idan Kaizerman , Amir Wachs
CPC classification number: G06T7/0004 , G06K9/52 , G06K9/685 , G06K2009/4666 , G06T7/0012 , G06T2207/10056 , G06T2207/20112 , G06T2207/30148
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.
Abstract translation: 一种用于分类晶片缺陷的方法，所述方法由计算机化系统执行，所述方法可以包括获得关于缺陷候选组的缺陷候选信息，其中所述缺陷候选信息包括所述组中每个缺陷候选的属性值; 响应于属于至少所选择的子组的缺陷候选的属性的值，由所述计算机化系统的处理器选择所选择的缺陷候选子组; 对所选子组的缺陷候选进行分类，以提供选定的子组分类结果; 重复，直到完成停止条件：响应于（a）至少属于附加选择的子组的缺陷候选的属性值，选择附加的选择的缺陷候选子组; 和（b）从至少一个其他选择的子组分类获得的分类结果; 并对附加选择的子组的缺陷候选进行分类，以提供附加的选择的子组分类结果。
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Patent Agency Ranking
公开(公告)号：US09286675B1
公开(公告)日：2016-03-15
申请号：US14522543
申请日：2014-10-23
Applicant: Applied Materials Israel Ltd.
Inventor： Saar Shabtay , Idan Kaizerman , Amir Wachs
CPC classification number: G06T7/0004 , G06K9/52 , G06K9/685 , G06K2009/4666 , G06T7/0012 , G06T2207/10056 , G06T2207/20112 , G06T2207/30148
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.
Abstract translation: 一种用于分类晶片缺陷的方法，所述方法由计算机化系统执行，所述方法可以包括获得关于缺陷候选组的缺陷候选信息，其中所述缺陷候选信息包括所述组中每个缺陷候选的属性值; 响应于属于至少所选择的子组的缺陷候选的属性的值，由所述计算机化系统的处理器选择所选择的缺陷候选子组; 对所选子组的缺陷候选进行分类，以提供选定的子组分类结果; 重复，直到完成停止条件：响应于（a）至少属于附加选择的子组的缺陷候选的属性值，选择附加的选择的缺陷候选子组; 和（b）从至少一个其他选择的子组分类获得的分类结果; 并对附加选择的子组的缺陷候选进行分类，以提供附加的选择的子组分类结果。
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17.发明授权公开(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.
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公开(公告)号：US10901402B2
公开(公告)日：2021-01-26
申请号：US16174070
申请日：2018-10-29
Applicant: Applied Materials Israel Ltd.
Inventor： Gadi Greenberg , Idan Kaizerman , Zeev Zohar
IPC: G06T7/00 , G05B19/418 , H01J37/00 , H01L21/66
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：US10818000B2
公开(公告)日：2020-10-27
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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20.发明授权公开(公告)号：US10663407B2
公开(公告)日：2020-05-26
申请号：US16227453
申请日：2018-12-20
Applicant: Applied Materials Israel Ltd.
Inventor： Idan Kaizerman , Mark Geshel
IPC: H01L21/66 , G06F30/398 , G01N21/95
Abstract: Data indicative of alignment targets may be received. Each alignment target may be associated with a target location on an object. Locations of the object to be inspected may be identified. An alignment target from the alignment targets may be selected. Each of the locations may be within a determined distance from the selected alignment target. An indication may be provided to align the object relative to an examination tool for inspecting the locations within the determined distance from the selected alignment target.
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