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    • 2. 发明申请
    • INTEGRATION OF AUTOMATIC AND MANUAL DEFECT CLASSIFICATION
    • 自动和手动缺陷分类的整合
    • US20130279794A1
    • 2013-10-24
    • US13451496
    • 2012-04-19
    • Gadi GreenbergIdan KaizermanEfrat Rozenman
    • Gadi GreenbergIdan KaizermanEfrat Rozenman
    • G06K9/00
    • G06T7/001G06K9/033G06K9/6269G06K9/6284G06T2207/10061G06T2207/30148
    • A method for defect classification includes storing definitions of defect classes in terms of a classification rules in a multi-dimensional feature space. Inspection data associated with defects detected in one or more samples under inspection is received. A plurality of first classification results is generated by applying an automatic classifier to the inspection data based on the definitions, the plurality of first classification results comprising a class label and a corresponding confidence level for a defect. Upon determining that a confidence level for a defect is below a predetermined confidence threshold, a plurality of second classification results are generated by applying at least one inspection modality to the defect. A report is generated comprising a distribution of the defects among the defect classes by combining the plurality of first classification results and the plurality of second classification results.
    • 一种用于缺陷分类的方法包括根据多维特征空间中的分类规则存储缺陷类的定义。 接收与在检查中的一个或多个样品中检测到的缺陷有关的检查数据。 通过基于定义应用自动分类器来生成多个第一分类结果,多个第一分类结果包括类别标签和相应的缺陷置信度。 在确定缺陷的置信水平低于预定置信度阈值时,通过对缺陷应用至少一种检查模式来生成多个第二分类结果。 通过组合多个第一分类结果和多个第二分类结果,生成包括缺陷类别中的缺陷的分布的报告。
    • 5. 发明申请
    • CLASSIFIER READINESS AND MAINTENANCE IN AUTOMATIC DEFECT CLASSIFICATION
    • 分类器在自动缺陷分类中的阅读和维护
    • US20130279796A1
    • 2013-10-24
    • US13452771
    • 2012-04-20
    • Idan KaizermanVladimir ShlainEfrat Rozenman
    • Idan KaizermanVladimir ShlainEfrat Rozenman
    • G06K9/62G06K9/00
    • G06K9/033G06K9/6256G06K9/6267G06T7/0004G06T7/001G06T2207/30148
    • A method for classification includes receiving inspection data associated with a plurality of defects found in one or more samples and receiving one or more benchmark classification comprising a class for each of the plurality of defects. a readiness criterion for one or more of the classes is evaluated based on the one or more benchmark classification results, wherein the readiness criterion comprises for each class, a suitability of the inspection data for training an automatic defect classifier for the class. A portion of the inspection data is selected corresponding to one or more defects associated with one or more classes that satisfy the readiness criterion. One or more automatic classifiers are trained for the one or more classes that satisfy the readiness criterion using the selected portion of the inspection data.
    • 一种用于分类的方法包括接收与一个或多个样本中发现的多个缺陷相关联的检查数据,并且接收一个或多个基准分类,其包括针对所述多个缺陷中的每一个的类别。 基于一个或多个基准分类结果来评估一个或多个类的准备标准,其中准备准则包括对于每个类别,用于训练用于该类的自动缺陷分类器的检查数据的适合性。 对应于与满足准备标准的一个或多个类别相关联的一个或多个缺陷来选择检查数据的一部分。 使用检查数据的所选部分,针对满足准备标准的一个或多个类训练一个或多个自动分类器。