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公开(公告)号：US20160328837A1
公开(公告)日：2016-11-10
申请号：US14749316
申请日：2015-06-24
Applicant: KLA-Tencor Corporation
Inventor： Li He , ChienHuei Adam Chen , Sankar Venkataraman , John R. Jordan, III , Huajun Ying , Sinha Harsh
CPC classification number: G06T7/0004 , G06K9/6256 , G06K9/6292 , G06K2009/6295 , G06T2207/20081 , G06T2207/30148
Abstract: Defect classification includes acquiring one or more images of a specimen, receiving a manual classification of one or more training defects based on one or more attributes of the one or more training defects, generating an ensemble learning classifier based on the received manual classification and the attributes of the one or more training defects, generating a confidence threshold for each defect type of the one or more training defects based on a received classification purity requirement, acquiring one or more images including one or more test defects, classifying the one or more test defects with the generated ensemble learning classifier, calculating a confidence level for each of the one or more test defects with the generated ensemble learning classifier and reporting one or more test defects having a confidence level below the generated confidence threshold via the user interface device for manual classification.
Abstract translation: 缺陷分类包括获取样本的一个或多个图像，基于一个或多个训练缺陷的一个或多个属性接收一个或多个训练缺陷的手动分类，基于所接收到的手动分类和属性生成集合学习分类器 的一个或多个训练缺陷，基于接收到的分类纯度要求，生成针对所述一个或多个训练缺陷的每个缺陷类型的置信阈值，获取包括一个或多个测试缺陷的一个或多个图像，分类一个或多个测试缺陷 利用所生成的集体学习分类器，利用所生成的集体学习分类器计算每个一个或多个测试缺陷的置信水平，并且经由用户界面设备报告具有低于生成的置信度阈值的置信水平的一个或多个测试缺陷以进行手动分类 。
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公开(公告)号：US10482590B2
公开(公告)日：2019-11-19
申请号：US15839690
申请日：2017-12-12
Applicant: KLA-Tencor Corporation
Inventor： Li He , Chien-Huei Adam Chen , Sankar Venkataraman , John R. Jordan , Huajun Ying , Sinha Harsh
Abstract: Defect classification includes acquiring one or more images of a specimen, receiving a manual classification of one or more training defects based on one or more attributes of the one or more training defects, generating an ensemble learning classifier based on the received manual classification and the attributes of the one or more training defects, generating a confidence threshold for each defect type of the one or more training defects based on a received classification purity requirement, acquiring one or more images including one or more test defects, classifying the one or more test defects with the generated ensemble learning classifier, calculating a confidence level for each of the one or more test defects with the generated ensemble learning classifier and reporting one or more test defects having a confidence level below the generated confidence threshold via the user interface device for manual classification.
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公开(公告)号：US20180114310A1
公开(公告)日：2018-04-26
申请号：US15839690
申请日：2017-12-12
Applicant: KLA-Tencor Corporation
Inventor： Li He , Chien-Huei Adam Chen , Sankar Venkataraman , John R. Jordan , Huajun Ying , Sinha Harsh
CPC classification number: G06T7/0004 , G06K9/6256 , G06K9/6292 , G06K2009/6295 , G06T2207/20081 , G06T2207/30148
Abstract: Defect classification includes acquiring one or more images of a specimen, receiving a manual classification of one or more training defects based on one or more attributes of the one or more training defects, generating an ensemble learning classifier based on the received manual classification and the attributes of the one or more training defects, generating a confidence threshold for each defect type of the one or more training defects based on a received classification purity requirement, acquiring one or more images including one or more test defects, classifying the one or more test defects with the generated ensemble learning classifier, calculating a confidence level for each of the one or more test defects with the generated ensemble learning classifier and reporting one or more test defects having a confidence level below the generated confidence threshold via the user interface device for manual classification.
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