JP2022512292A5 - - Google Patents
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- Publication number
- JP2022512292A5 JP2022512292A5 JP2021524054A JP2021524054A JP2022512292A5 JP 2022512292 A5 JP2022512292 A5 JP 2022512292A5 JP 2021524054 A JP2021524054 A JP 2021524054A JP 2021524054 A JP2021524054 A JP 2021524054A JP 2022512292 A5 JP2022512292 A5 JP 2022512292A5
- Authority
- JP
- Japan
- Prior art keywords
- defects
- class
- attribute
- belonging
- subset
- Prior art date
Links
Applications Claiming Priority (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US16/228,676 | 2018-12-20 | ||
| US16/228,676 US11321633B2 (en) | 2018-12-20 | 2018-12-20 | Method of classifying defects in a specimen semiconductor examination and system thereof |
| PCT/IL2019/051284 WO2020129041A1 (en) | 2018-12-20 | 2019-11-24 | Classifying defects in a semiconductor specimen |
Publications (4)
| Publication Number | Publication Date |
|---|---|
| JP2022512292A JP2022512292A (ja) | 2022-02-03 |
| JPWO2020129041A5 JPWO2020129041A5 (https=) | 2022-08-30 |
| JP2022512292A5 true JP2022512292A5 (https=) | 2022-08-30 |
| JP7254921B2 JP7254921B2 (ja) | 2023-04-10 |
Family
ID=71097693
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP2021524054A Active JP7254921B2 (ja) | 2018-12-20 | 2019-11-24 | 半導体試料の欠陥の分類 |
Country Status (6)
| Country | Link |
|---|---|
| US (1) | US11321633B2 (https=) |
| JP (1) | JP7254921B2 (https=) |
| KR (1) | KR102530950B1 (https=) |
| CN (1) | CN112805719B (https=) |
| TW (1) | TWI791930B (https=) |
| WO (1) | WO2020129041A1 (https=) |
Families Citing this family (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110286279B (zh) * | 2019-06-05 | 2021-03-16 | 武汉大学 | 基于极端树与堆栈式稀疏自编码算法的电力电子电路故障诊断方法 |
| US11379969B2 (en) * | 2019-08-01 | 2022-07-05 | Kla Corporation | Method for process monitoring with optical inspections |
| US11568317B2 (en) | 2020-05-21 | 2023-01-31 | Paypal, Inc. | Enhanced gradient boosting tree for risk and fraud modeling |
| TWI770817B (zh) * | 2021-02-09 | 2022-07-11 | 鴻海精密工業股份有限公司 | 瑕疵檢測方法、電子裝置及存儲介質 |
| CN119359475A (zh) * | 2024-12-23 | 2025-01-24 | 济南农智信息科技有限公司 | 一种边坡土壤肥力预测方法 |
Family Cites Families (22)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030204507A1 (en) | 2002-04-25 | 2003-10-30 | Li Jonathan Qiang | Classification of rare events with high reliability |
| JP4118703B2 (ja) * | 2002-05-23 | 2008-07-16 | 株式会社日立ハイテクノロジーズ | 欠陥分類装置及び欠陥自動分類方法並びに欠陥検査方法及び処理装置 |
| US7756320B2 (en) | 2003-03-12 | 2010-07-13 | Hitachi High-Technologies Corporation | Defect classification using a logical equation for high stage classification |
| JP4443270B2 (ja) | 2003-03-12 | 2010-03-31 | 株式会社日立ハイテクノロジーズ | 欠陥分類方法 |
| US20090097741A1 (en) * | 2006-03-30 | 2009-04-16 | Mantao Xu | Smote algorithm with locally linear embedding |
| JP5156452B2 (ja) * | 2008-03-27 | 2013-03-06 | 東京エレクトロン株式会社 | 欠陥分類方法、プログラム、コンピュータ記憶媒体及び欠陥分類装置 |
| CN102095731A (zh) * | 2010-12-02 | 2011-06-15 | 山东轻工业学院 | 在纸张缺陷视觉检测中识别不同缺陷类型的系统及方法 |
| TWI574136B (zh) * | 2012-02-03 | 2017-03-11 | 應用材料以色列公司 | 基於設計之缺陷分類之方法及系統 |
| US9224104B2 (en) * | 2013-09-24 | 2015-12-29 | International Business Machines Corporation | Generating data from imbalanced training data sets |
| US9489599B2 (en) * | 2013-11-03 | 2016-11-08 | Kla-Tencor Corp. | Decision tree construction for automatic classification of defects on semiconductor wafers |
| US9286675B1 (en) * | 2014-10-23 | 2016-03-15 | Applied Materials Israel Ltd. | Iterative defect filtering process |
| CN104458755B (zh) * | 2014-11-26 | 2017-02-22 | 吴晓军 | 一种基于机器视觉的多类型材质表面缺陷检测方法 |
| US20160189055A1 (en) * | 2014-12-31 | 2016-06-30 | Applied Materials Israel Ltd. | Tuning of parameters for automatic classification |
| US9898811B2 (en) | 2015-05-08 | 2018-02-20 | Kla-Tencor Corporation | Method and system for defect classification |
| US10436720B2 (en) * | 2015-09-18 | 2019-10-08 | KLA-Tenfor Corp. | Adaptive automatic defect classification |
| CN105677564A (zh) * | 2016-01-04 | 2016-06-15 | 中国石油大学(华东) | 基于改进的Adaboost软件缺陷不平衡数据分类方法 |
| US10565513B2 (en) * | 2016-09-19 | 2020-02-18 | Applied Materials, Inc. | Time-series fault detection, fault classification, and transition analysis using a K-nearest-neighbor and logistic regression approach |
| US10031997B1 (en) * | 2016-11-29 | 2018-07-24 | Taiwan Semiconductor Manufacturing Co., Ltd. | Forecasting wafer defects using frequency domain analysis |
| CN106778853A (zh) * | 2016-12-07 | 2017-05-31 | 中南大学 | 基于权重聚类和欠抽样的不平衡数据分类方法 |
| US11416979B2 (en) | 2017-01-18 | 2022-08-16 | Asml Netherlands B.V. | Defect displaying method |
| CN108596199A (zh) * | 2017-12-29 | 2018-09-28 | 北京交通大学 | 基于EasyEnsemble算法和SMOTE算法的不均衡数据分类方法 |
| CN108470187A (zh) * | 2018-02-26 | 2018-08-31 | 华南理工大学 | 一种基于扩充训练数据集的类别不平衡问题分类方法 |
-
2018
- 2018-12-20 US US16/228,676 patent/US11321633B2/en active Active
-
2019
- 2019-11-24 CN CN201980065723.0A patent/CN112805719B/zh active Active
- 2019-11-24 WO PCT/IL2019/051284 patent/WO2020129041A1/en not_active Ceased
- 2019-11-24 KR KR1020217015166A patent/KR102530950B1/ko active Active
- 2019-11-24 JP JP2021524054A patent/JP7254921B2/ja active Active
- 2019-12-17 TW TW108146199A patent/TWI791930B/zh active
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