JP7633094B2 - 弱いラベル付けを使用した半導体試料内の欠陥の検出 - Google Patents
弱いラベル付けを使用した半導体試料内の欠陥の検出 Download PDFInfo
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- JP7633094B2 JP7633094B2 JP2021093501A JP2021093501A JP7633094B2 JP 7633094 B2 JP7633094 B2 JP 7633094B2 JP 2021093501 A JP2021093501 A JP 2021093501A JP 2021093501 A JP2021093501 A JP 2021093501A JP 7633094 B2 JP7633094 B2 JP 7633094B2
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- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
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- G06T7/0004—Industrial image inspection
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
- G01N21/9501—Semiconductor wafers
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- H—ELECTRICITY
- H10—SEMICONDUCTOR DEVICES; ELECTRIC SOLID-STATE DEVICES NOT OTHERWISE PROVIDED FOR
- H10P—GENERIC PROCESSES OR APPARATUS FOR THE MANUFACTURE OR TREATMENT OF DEVICES COVERED BY CLASS H10
- H10P74/00—Testing or measuring during manufacture or treatment of wafers, substrates or devices
- H10P74/20—Testing or measuring during manufacture or treatment of wafers, substrates or devices characterised by the properties tested or measured, e.g. structural or electrical properties
- H10P74/203—Structural properties, e.g. testing or measuring thicknesses, line widths, warpage, bond strengths or physical defects
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- Investigating Materials By The Use Of Optical Means Adapted For Particular Applications (AREA)
- Testing Or Measuring Of Semiconductors Or The Like (AREA)
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Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US16/892,139 US11379972B2 (en) | 2020-06-03 | 2020-06-03 | Detecting defects in semiconductor specimens using weak labeling |
| US16/892,139 | 2020-06-03 |
Publications (3)
| Publication Number | Publication Date |
|---|---|
| JP2021190716A JP2021190716A (ja) | 2021-12-13 |
| JP2021190716A5 JP2021190716A5 (https=) | 2024-06-10 |
| JP7633094B2 true JP7633094B2 (ja) | 2025-02-19 |
Family
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Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP2021093501A Active JP7633094B2 (ja) | 2020-06-03 | 2021-06-03 | 弱いラベル付けを使用した半導体試料内の欠陥の検出 |
Country Status (5)
| Country | Link |
|---|---|
| US (2) | US11379972B2 (https=) |
| JP (1) | JP7633094B2 (https=) |
| KR (1) | KR102749767B1 (https=) |
| CN (2) | CN118297906B (https=) |
| TW (1) | TWI864281B (https=) |
Families Citing this family (20)
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| US11816411B2 (en) * | 2020-01-29 | 2023-11-14 | Taiwan Semiconductor Manufacturing Co., Ltd. | Method and system for semiconductor wafer defect review |
| US11379972B2 (en) * | 2020-06-03 | 2022-07-05 | Applied Materials Israel Ltd. | Detecting defects in semiconductor specimens using weak labeling |
| US11493901B2 (en) * | 2020-09-24 | 2022-11-08 | International Business Machines Corporation | Detection of defect in edge device manufacturing by artificial intelligence |
| US20220101114A1 (en) * | 2020-09-27 | 2022-03-31 | Kla Corporation | Interpretable deep learning-based defect detection and classification |
| US12567233B2 (en) * | 2020-11-09 | 2026-03-03 | Canon U.S.A., Inc. | Using activation maps to detect best areas of an image for prediction of noise levels |
| US12462074B2 (en) * | 2021-01-22 | 2025-11-04 | Nvidia Corporation | Object simulation using real-world environments |
| US12430563B2 (en) * | 2021-07-29 | 2025-09-30 | GE Precision Healthcare LLC | Learning-based clean data selection |
| CN115706819B (zh) * | 2021-08-17 | 2024-12-31 | 鸿富锦精密工业(深圳)有限公司 | 网页视频播放方法、装置、电子设备及存储介质 |
| TWI767828B (zh) * | 2021-08-27 | 2022-06-11 | 開必拓數據股份有限公司 | 應用於具有卷對卷機構的設備的馬達控制系統 |
| US20240013365A9 (en) * | 2021-10-04 | 2024-01-11 | Kla Corporation | Unsupervised or self-supervised deep learning for semiconductor-based applications |
| TWI823159B (zh) * | 2021-10-20 | 2023-11-21 | 開必拓數據股份有限公司 | 具人機互動功能的瑕疵檢測系統 |
| US11789069B2 (en) * | 2021-12-03 | 2023-10-17 | International Business Machines Corporation | Mixed high-resolution and low-resolution inspection for tamper detection |
| CN115061427B (zh) * | 2022-06-28 | 2023-04-14 | 浙江同发塑机有限公司 | 吹塑机的料层均匀性控制系统及其控制方法 |
| KR20240028665A (ko) * | 2022-08-25 | 2024-03-05 | 한국전자통신연구원 | 딥러닝 서비스를 제공하기 위한 신경망 모델 배포 방법 및 장치 |
| JP2024082013A (ja) * | 2022-12-07 | 2024-06-19 | 株式会社Screenホールディングス | 画像処理装置、特徴抽出器の学習方法、識別器の更新方法、および画像処理方法 |
| KR20240096217A (ko) * | 2022-12-19 | 2024-06-26 | 삼성전자주식회사 | 제조 공정의 이상 여부를 판단하는 방법 및 장치 |
| CN116046810B (zh) * | 2023-04-03 | 2023-06-23 | 云南通衢工程检测有限公司 | 基于rpc盖板破坏荷载的无损检测方法 |
| WO2025011912A1 (en) * | 2023-07-13 | 2025-01-16 | Asml Netherlands B.V. | Systems and methods for defect inspection in charged-particle systems |
| KR102740270B1 (ko) * | 2023-10-19 | 2024-12-10 | 주식회사 에이아이비즈 | 웨이퍼맵의 패턴을 분류하기 위한 모델을 학습시키는 방법, 장치 및 프로그램 |
| US20250253121A1 (en) * | 2024-02-07 | 2025-08-07 | Kla Corporation | Systems and methods of sem inspection using selective scan approach |
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| US11379972B2 (en) * | 2020-06-03 | 2022-07-05 | Applied Materials Israel Ltd. | Detecting defects in semiconductor specimens using weak labeling |
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2020
- 2020-06-03 US US16/892,139 patent/US11379972B2/en active Active
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2021
- 2021-04-16 KR KR1020210049665A patent/KR102749767B1/ko active Active
- 2021-04-26 CN CN202410416642.3A patent/CN118297906B/zh active Active
- 2021-04-26 TW TW110114852A patent/TWI864281B/zh active
- 2021-04-26 CN CN202110455269.9A patent/CN113763312B/zh active Active
- 2021-06-03 JP JP2021093501A patent/JP7633094B2/ja active Active
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2022
- 2022-05-23 US US17/751,507 patent/US11790515B2/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160300338A1 (en) | 2015-04-13 | 2016-10-13 | Anchor Semiconductor Inc. | Pattern weakness and strength detection and tracking during a semiconductor device fabrication process |
| WO2019050992A1 (en) | 2017-09-06 | 2019-03-14 | Kla-Tencor Corporation | UNIFIED NEURONAL NETWORK FOR DETECTION AND CLASSIFICATION OF DEFECTS |
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| Publication number | Publication date |
|---|---|
| JP2021190716A (ja) | 2021-12-13 |
| US20220301151A1 (en) | 2022-09-22 |
| CN118297906B (zh) | 2025-07-29 |
| CN113763312A (zh) | 2021-12-07 |
| CN118297906A (zh) | 2024-07-05 |
| CN113763312B (zh) | 2024-04-19 |
| TWI864281B (zh) | 2024-12-01 |
| US20210383530A1 (en) | 2021-12-09 |
| KR102749767B1 (ko) | 2025-01-07 |
| US11790515B2 (en) | 2023-10-17 |
| TW202147163A (zh) | 2021-12-16 |
| KR20210150970A (ko) | 2021-12-13 |
| US11379972B2 (en) | 2022-07-05 |
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