CN112823412B - 用于半导体衬底的临界尺寸测量的基于深度学习的自适应关注区域 - Google Patents

用于半导体衬底的临界尺寸测量的基于深度学习的自适应关注区域 Download PDF

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CN112823412B
CN112823412B CN201980065799.3A CN201980065799A CN112823412B CN 112823412 B CN112823412 B CN 112823412B CN 201980065799 A CN201980065799 A CN 201980065799A CN 112823412 B CN112823412 B CN 112823412B
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CN112823412A (zh
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A·亚提
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KLA Corp
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    • H10P74/27—Structural arrangements therefor
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    • G06F18/00—Pattern recognition
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    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
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    • 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
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    • H10P74/23—Testing or measuring during manufacture or treatment of wafers, substrates or devices characterised by multiple measurements, corrections, marking or sorting processes
    • H10P74/232—Testing or measuring during manufacture or treatment of wafers, substrates or devices characterised by multiple measurements, corrections, marking or sorting processes comprising connection or disconnection of parts of a device in response to a measurement
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    • H10P74/238—Testing or measuring during manufacture or treatment of wafers, substrates or devices characterised by multiple measurements, corrections, marking or sorting processes comprising acting in response to an ongoing measurement without interruption of processing, e.g. endpoint detection or in-situ thickness measurement
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    • G06T2207/00—Indexing scheme for image analysis or image enhancement
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    • G06T2207/20104—Interactive definition of region of interest [ROI]
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
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    • G06T2207/30148—Semiconductor; IC; Wafer

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  • Testing Or Measuring Of Semiconductors Or The Like (AREA)
  • Length-Measuring Devices Using Wave Or Particle Radiation (AREA)
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CN201980065799.3A 2018-10-08 2019-10-01 用于半导体衬底的临界尺寸测量的基于深度学习的自适应关注区域 Active CN112823412B (zh)

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IN201841037993 2018-10-08
IN201841037993 2018-10-08
US201862770712P 2018-11-21 2018-11-21
US62/770,712 2018-11-21
US16/420,408 US11094053B2 (en) 2018-10-08 2019-05-23 Deep learning based adaptive regions of interest for critical dimension measurements of semiconductor substrates
US16/420,408 2019-05-23
PCT/US2019/053922 WO2020076544A1 (en) 2018-10-08 2019-10-01 Deep learning based adaptive regions of interest for critical dimension measurements of semiconductor substrates

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Families Citing this family (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2021026926A (ja) * 2019-08-07 2021-02-22 株式会社日立ハイテク 画像生成方法、非一時的コンピューター可読媒体、及びシステム
CN116880134A (zh) * 2020-01-07 2023-10-13 诺威有限公司 用于ocd计量的方法
CN113809117B (zh) * 2020-06-16 2023-12-22 联华电子股份有限公司 半导体元件及其制作方法
US11967058B2 (en) 2020-06-24 2024-04-23 Kla Corporation Semiconductor overlay measurements using machine learning
CN113393447B (zh) * 2021-06-24 2022-08-02 四川启睿克科技有限公司 基于深度学习的针尖正位度检测方法及系统
US12223752B2 (en) 2021-09-30 2025-02-11 Fei Company Data acquisition in charged particle microscopy
WO2024049199A1 (ko) * 2022-08-31 2024-03-07 주식회사 엘지에너지솔루션 학습 모델 기반의 치수 측정 장치 및 방법
WO2024065645A1 (zh) * 2022-09-30 2024-04-04 北京京东方技术开发有限公司 图像文本匹配模型的训练方法、装置、设备及存储介质
US20240161264A1 (en) * 2022-11-15 2024-05-16 Micron Technology, Inc. Defect characterization in semiconductor devices based on image processing
US12449379B2 (en) 2023-05-25 2025-10-21 Applied Materials, Inc. Machine learning model training
US20240394509A1 (en) * 2023-05-25 2024-11-28 Applied Materials, Inc. Generating synthetic microspy images of substrates

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107305636A (zh) * 2016-04-22 2017-10-31 株式会社日立制作所 目标识别方法、目标识别装置、终端设备和目标识别系统
WO2017200524A1 (en) * 2016-05-16 2017-11-23 United Technologies Corporation Deep convolutional neural networks for crack detection from image data
CN107820620A (zh) * 2015-05-08 2018-03-20 科磊股份有限公司 用于缺陷分类的方法和系统
CN108027499A (zh) * 2015-09-23 2018-05-11 科磊股份有限公司 用于多波束扫描式电子显微系统的聚焦调整的方法及系统

Family Cites Families (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP5238465B2 (ja) 2008-11-25 2013-07-17 株式会社東芝 パターン形状の評価方法及びこれを利用したパターン形状の評価装置
US9189844B2 (en) 2012-10-15 2015-11-17 Kla-Tencor Corp. Detecting defects on a wafer using defect-specific information
US9490182B2 (en) * 2013-12-23 2016-11-08 Kla-Tencor Corporation Measurement of multiple patterning parameters
US9087176B1 (en) * 2014-03-06 2015-07-21 Kla-Tencor Corporation Statistical overlay error prediction for feed forward and feedback correction of overlay errors, root cause analysis and process control
US10127653B2 (en) 2014-07-22 2018-11-13 Kla-Tencor Corp. Determining coordinates for an area of interest on a specimen
KR102238742B1 (ko) 2014-09-11 2021-04-12 삼성전자주식회사 마스크 패턴의 측정 관심 영역 그룹화 방법 및 이를 이용한 마스크 패턴의 선폭 계측 방법
US10483081B2 (en) 2014-10-22 2019-11-19 Kla-Tencor Corp. Self directed metrology and pattern classification
US10267746B2 (en) * 2014-10-22 2019-04-23 Kla-Tencor Corp. Automated pattern fidelity measurement plan generation
TWI684225B (zh) * 2015-08-28 2020-02-01 美商克萊譚克公司 自定向計量和圖樣分類
US9875534B2 (en) * 2015-09-04 2018-01-23 Kla-Tencor Corporation Techniques and systems for model-based critical dimension measurements
US10181185B2 (en) * 2016-01-11 2019-01-15 Kla-Tencor Corp. Image based specimen process control
KR102606308B1 (ko) 2016-06-28 2023-11-24 삼성전자주식회사 포토 마스크의 제조 방법, 패턴 형성 방법 및 반도체 장치의 제조 방법
US10402688B2 (en) * 2016-12-07 2019-09-03 Kla-Tencor Corporation Data augmentation for convolutional neural network-based defect inspection
US10565702B2 (en) * 2017-01-30 2020-02-18 Dongfang Jingyuan Electron Limited Dynamic updates for the inspection of integrated circuits

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107820620A (zh) * 2015-05-08 2018-03-20 科磊股份有限公司 用于缺陷分类的方法和系统
CN108027499A (zh) * 2015-09-23 2018-05-11 科磊股份有限公司 用于多波束扫描式电子显微系统的聚焦调整的方法及系统
CN107305636A (zh) * 2016-04-22 2017-10-31 株式会社日立制作所 目标识别方法、目标识别装置、终端设备和目标识别系统
WO2017200524A1 (en) * 2016-05-16 2017-11-23 United Technologies Corporation Deep convolutional neural networks for crack detection from image data

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US11094053B2 (en) 2021-08-17
US20200111206A1 (en) 2020-04-09
TWI808265B (zh) 2023-07-11
KR20210057203A (ko) 2021-05-20
EP3853885B1 (en) 2025-07-30
TW202029371A (zh) 2020-08-01
JP2022504505A (ja) 2022-01-13
WO2020076544A1 (en) 2020-04-16
JP7284813B2 (ja) 2023-05-31
KR102576880B1 (ko) 2023-09-08
CN112823412A (zh) 2021-05-18
EP3853885A1 (en) 2021-07-28
EP3853885A4 (en) 2022-07-13

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