CN104217224B8 - 使用多机器学习核的光刻热点检测 - Google Patents
使用多机器学习核的光刻热点检测 Download PDFInfo
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- CN104217224B8 CN104217224B8 CN201410240890.3A CN201410240890A CN104217224B8 CN 104217224 B8 CN104217224 B8 CN 104217224B8 CN 201410240890 A CN201410240890 A CN 201410240890A CN 104217224 B8 CN104217224 B8 CN 104217224B8
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- 238000010801 machine learning Methods 0.000 title 1
- 238000001514 detection method Methods 0.000 abstract 2
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
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- G—PHYSICS
- G03—PHOTOGRAPHY; CINEMATOGRAPHY; ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ELECTROGRAPHY; HOLOGRAPHY
- G03F—PHOTOMECHANICAL PRODUCTION OF TEXTURED OR PATTERNED SURFACES, e.g. FOR PRINTING, FOR PROCESSING OF SEMICONDUCTOR DEVICES; MATERIALS THEREFOR; ORIGINALS THEREFOR; APPARATUS SPECIALLY ADAPTED THEREFOR
- G03F7/00—Photomechanical, e.g. photolithographic, production of textured or patterned surfaces, e.g. printing surfaces; Materials therefor, e.g. comprising photoresists; Apparatus specially adapted therefor
- G03F7/70—Microphotolithographic exposure; Apparatus therefor
- G03F7/70425—Imaging strategies, e.g. for increasing throughput or resolution, printing product fields larger than the image field or compensating lithography- or non-lithography errors, e.g. proximity correction, mix-and-match, stitching or double patterning
- G03F7/70433—Layout for increasing efficiency or for compensating imaging errors, e.g. layout of exposure fields for reducing focus errors; Use of mask features for increasing efficiency or for compensating imaging errors
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- G—PHYSICS
- G03—PHOTOGRAPHY; CINEMATOGRAPHY; ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ELECTROGRAPHY; HOLOGRAPHY
- G03F—PHOTOMECHANICAL PRODUCTION OF TEXTURED OR PATTERNED SURFACES, e.g. FOR PRINTING, FOR PROCESSING OF SEMICONDUCTOR DEVICES; MATERIALS THEREFOR; ORIGINALS THEREFOR; APPARATUS SPECIALLY ADAPTED THEREFOR
- G03F7/00—Photomechanical, e.g. photolithographic, production of textured or patterned surfaces, e.g. printing surfaces; Materials therefor, e.g. comprising photoresists; Apparatus specially adapted therefor
- G03F7/70—Microphotolithographic exposure; Apparatus therefor
- G03F7/70483—Information management; Active and passive control; Testing; Wafer monitoring, e.g. pattern monitoring
- G03F7/70491—Information management, e.g. software; Active and passive control, e.g. details of controlling exposure processes or exposure tool monitoring processes
- G03F7/705—Modelling or simulating from physical phenomena up to complete wafer processes or whole workflow in wafer productions
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
- G06N20/10—Machine learning using kernel methods, e.g. support vector machines [SVM]
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
- G06T7/001—Industrial image inspection using an image reference approach
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
- G06F18/2411—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on the proximity to a decision surface, e.g. support vector machines
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
- G06T2207/30144—Printing quality
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- Data Mining & Analysis (AREA)
- Mathematical Physics (AREA)
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- Quality & Reliability (AREA)
- Image Analysis (AREA)
- Preparing Plates And Mask In Photomechanical Process (AREA)
- Multimedia (AREA)
- Exposure And Positioning Against Photoresist Photosensitive Materials (AREA)
- Computational Linguistics (AREA)
- Design And Manufacture Of Integrated Circuits (AREA)
Abstract
热点检测系统根据热点训练数据的拓扑将热点训练数据集分类成多个热点簇,其中热点簇与不同的热点拓扑相关联,并且热点检测系统根据非热点训练数据的拓扑将非热点训练数据集分类成多个非热点簇,其中非热点簇与不同的拓扑相关联。该系统从热点簇并且从非热点簇的形心中提取拓扑关键特征和非拓扑关键特征。该系统还创建被配置为识别热点的多个核,其中使用所提取的非热点簇的形心的关键特征以及从热点簇中的一个热点簇所提取的关键特征来构造每个核,并且每个核被配置为识别与其他核被配置用于识别的热点拓扑不同的热点拓扑。
Priority Applications (1)
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CN201810720254.9A CN109242108B (zh) | 2013-05-30 | 2014-05-30 | 使用多机器学习核的光刻热点检测 |
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US201361828915P | 2013-05-30 | 2013-05-30 | |
US61/828,915 | 2013-05-30 |
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CN201810720254.9A Division CN109242108B (zh) | 2013-05-30 | 2014-05-30 | 使用多机器学习核的光刻热点检测 |
Publications (3)
Publication Number | Publication Date |
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CN104217224A CN104217224A (zh) | 2014-12-17 |
CN104217224B CN104217224B (zh) | 2018-07-17 |
CN104217224B8 true CN104217224B8 (zh) | 2018-11-23 |
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CN201810720254.9A Active CN109242108B (zh) | 2013-05-30 | 2014-05-30 | 使用多机器学习核的光刻热点检测 |
CN201410240890.3A Active CN104217224B8 (zh) | 2013-05-30 | 2014-05-30 | 使用多机器学习核的光刻热点检测 |
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CN201810720254.9A Active CN109242108B (zh) | 2013-05-30 | 2014-05-30 | 使用多机器学习核的光刻热点检测 |
Country Status (3)
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US (2) | US20140358830A1 (zh) |
CN (2) | CN109242108B (zh) |
TW (1) | TWI554824B (zh) |
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WO2016096309A1 (en) * | 2014-12-15 | 2016-06-23 | Asml Netherlands B.V. | Optimization based on machine learning |
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US10546246B2 (en) | 2015-09-18 | 2020-01-28 | International Business Machines Corporation | Enhanced kernel representation for processing multimodal data |
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US11922313B2 (en) | 2016-02-11 | 2024-03-05 | William Marsh Rice University | Partitioned machine learning architecture |
US11443083B2 (en) * | 2016-05-12 | 2022-09-13 | Asml Netherlands B.V. | Identification of hot spots or defects by machine learning |
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CN111051993B (zh) * | 2017-09-08 | 2022-06-28 | Asml荷兰有限公司 | 用于机器学习辅助的光学邻近误差校正的训练方法 |
US11022966B1 (en) * | 2017-12-15 | 2021-06-01 | Synopsys, Inc. | Method of modeling e-beam photomask manufacturing process using image-based artificial neural networks |
CN108053397B (zh) * | 2017-12-19 | 2022-04-26 | 上海集成电路研发中心有限公司 | 一种采用支持向量机检测光刻薄弱点的方法 |
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US10621302B2 (en) * | 2018-06-27 | 2020-04-14 | International Business Machines Corporation | Classification and localization of hotspots in integrated physical design layouts |
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TWI738169B (zh) * | 2019-01-29 | 2021-09-01 | 荷蘭商Asml荷蘭公司 | 用於為佈局圖案化程序判定訓練圖案之方法及相關的電腦程式產品 |
US10762618B1 (en) * | 2019-02-14 | 2020-09-01 | United Microelectronics Corp. | Mask weak pattern recognition apparatus and mask weak pattern recognition method |
KR20210116613A (ko) * | 2019-02-21 | 2021-09-27 | 에이에스엠엘 네델란즈 비.브이. | 마스크에 대한 광학 근접 보정을 결정하기 위한 머신 러닝 모델의 트레이닝 방법 |
US11263496B2 (en) * | 2019-02-25 | 2022-03-01 | D2S, Inc. | Methods and systems to classify features in electronic designs |
US11182929B2 (en) | 2019-02-25 | 2021-11-23 | Center For Deep Learning In Electronics Manufacturing, Inc. | Methods and systems for compressing shape data for electronic designs |
US12092963B2 (en) * | 2019-04-25 | 2024-09-17 | Asml Netherlands B.V. | Method of determining characteristic of patterning process based on defect for reducing hotspot |
US10831976B1 (en) | 2019-05-30 | 2020-11-10 | International Business Machines Corporation | Predicting local layout effects in circuit design patterns |
CN113297263A (zh) * | 2020-04-01 | 2021-08-24 | 阿里巴巴集团控股有限公司 | 数据处理方法、装置、系统、电子设备及存储介质 |
KR20230051510A (ko) * | 2020-08-19 | 2023-04-18 | 에이에스엠엘 네델란즈 비.브이. | 이미지 기반 패턴 선택을 위한 시스템, 제품 및 방법 |
US20220067426A1 (en) * | 2020-08-28 | 2022-03-03 | Siemens Industry Software Inc. | Separation distance between feature vectors for semi-supervised hotspot detection and classification |
CN113674235B (zh) * | 2021-08-15 | 2023-10-10 | 上海立芯软件科技有限公司 | 一种基于主动熵采样和模型校准的低代价光刻热点检测方法 |
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2014
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- 2014-05-29 TW TW103118882A patent/TWI554824B/zh active
- 2014-05-30 CN CN201810720254.9A patent/CN109242108B/zh active Active
- 2014-05-30 CN CN201410240890.3A patent/CN104217224B8/zh active Active
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2019
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Also Published As
Publication number | Publication date |
---|---|
CN109242108A (zh) | 2019-01-18 |
US11403564B2 (en) | 2022-08-02 |
CN104217224B (zh) | 2018-07-17 |
CN109242108B (zh) | 2022-07-12 |
US20140358830A1 (en) | 2014-12-04 |
CN104217224A (zh) | 2014-12-17 |
TWI554824B (zh) | 2016-10-21 |
US20190287021A1 (en) | 2019-09-19 |
TW201510636A (zh) | 2015-03-16 |
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