JP6845327B2 - 畳み込み式ニューラルネットワークに基づく欠陥検査のためのデータ増強 - Google Patents

畳み込み式ニューラルネットワークに基づく欠陥検査のためのデータ増強 Download PDF

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JP6845327B2
JP6845327B2 JP2019530496A JP2019530496A JP6845327B2 JP 6845327 B2 JP6845327 B2 JP 6845327B2 JP 2019530496 A JP2019530496 A JP 2019530496A JP 2019530496 A JP2019530496 A JP 2019530496A JP 6845327 B2 JP6845327 B2 JP 6845327B2
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ビョルン ブラウアー
ビョルン ブラウアー
ヴィジャヤクマル ラマチャンドラン
ヴィジャヤクマル ラマチャンドラン
フォード リチャード ウォーリング
フォード リチャード ウォーリング
スコット エー ヤング
スコット エー ヤング
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KLA Corp
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    • G06—COMPUTING OR CALCULATING; 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
    • H—ELECTRICITY
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    • 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
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/24—Classification techniques
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    • G06F18/2413—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on distances to training or reference patterns
    • G06F18/24133—Distances to prototypes
    • G06F18/24143—Distances to neighbourhood prototypes, e.g. restricted Coulomb energy networks [RCEN]
    • G—PHYSICS
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    • G06N3/0464—Convolutional networks [CNN, ConvNet]
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    • G06N3/00—Computing arrangements based on biological models
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    • G06N3/08—Learning methods
    • G06N3/082—Learning methods modifying the architecture, e.g. adding, deleting or silencing nodes or connections
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
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    • G06N3/08—Learning methods
    • G06N3/09—Supervised learning
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/096—Transfer learning
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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
    • G06T7/0008—Industrial image inspection checking presence/absence
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/764—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
    • 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
    • H10P72/00—Handling or holding of wafers, substrates or devices during manufacture or treatment thereof
    • H10P72/06—Apparatus for monitoring, sorting, marking, testing or measuring
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    • 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
    • H10P74/23—Testing or measuring during manufacture or treatment of wafers, substrates or devices characterised by multiple measurements, corrections, marking or sorting processes
    • H10P74/235—Testing or measuring during manufacture or treatment of wafers, substrates or devices characterised by multiple measurements, corrections, marking or sorting processes comprising optical enhancement of defects or not-directly-visible states
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    • 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
    • H10P74/27—Structural arrangements therefor
    • 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
    • G06T2207/20—Special algorithmic details
    • G06T2207/20021—Dividing image into blocks, subimages or windows
    • 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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    • G06T2207/20084—Artificial neural networks [ANN]
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    • G06—COMPUTING OR CALCULATING; 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
    • G06T2207/30148—Semiconductor; IC; Wafer
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V2201/00—Indexing scheme relating to image or video recognition or understanding
    • G06V2201/06—Recognition of objects for industrial automation

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  • Engineering & Computer Science (AREA)
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  • Evolutionary Biology (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Multimedia (AREA)
  • Testing Or Measuring Of Semiconductors Or The Like (AREA)
  • Investigating Materials By The Use Of Optical Means Adapted For Particular Applications (AREA)
  • Image Analysis (AREA)
  • Manufacturing & Machinery (AREA)
JP2019530496A 2016-12-07 2017-12-06 畳み込み式ニューラルネットワークに基づく欠陥検査のためのデータ増強 Active JP6845327B2 (ja)

Applications Claiming Priority (5)

Application Number Priority Date Filing Date Title
US201662430925P 2016-12-07 2016-12-07
US62/430,925 2016-12-07
US15/720,272 US10402688B2 (en) 2016-12-07 2017-09-29 Data augmentation for convolutional neural network-based defect inspection
US15/720,272 2017-09-29
PCT/US2017/064947 WO2018106827A1 (en) 2016-12-07 2017-12-06 Data augmentation for convolutional neural network-based defect inspection

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JP2020501154A JP2020501154A (ja) 2020-01-16
JP2020501154A5 JP2020501154A5 (https=) 2021-01-21
JP6845327B2 true JP6845327B2 (ja) 2021-03-17

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US (1) US10402688B2 (https=)
JP (1) JP6845327B2 (https=)
KR (1) KR102312242B1 (https=)
CN (1) CN110168710B (https=)
IL (1) IL267040B (https=)
TW (1) TWI731198B (https=)
WO (1) WO2018106827A1 (https=)

Families Citing this family (74)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2017191501A (ja) * 2016-04-14 2017-10-19 キヤノン株式会社 情報処理装置、情報処理方法及びプログラム
US11868804B1 (en) 2019-11-18 2024-01-09 Groq, Inc. Processor instruction dispatch configuration
US11243880B1 (en) 2017-09-15 2022-02-08 Groq, Inc. Processor architecture
US11360934B1 (en) 2017-09-15 2022-06-14 Groq, Inc. Tensor streaming processor architecture
US11170307B1 (en) 2017-09-21 2021-11-09 Groq, Inc. Predictive model compiler for generating a statically scheduled binary with known resource constraints
EP3489892B1 (en) * 2017-11-24 2022-01-05 Ficosa Adas, S.L.U. Determining clean or dirty captured images
KR20190084167A (ko) * 2017-12-21 2019-07-16 주식회사 고영테크놀러지 인쇄 회로 기판 검사 장치, 스크린 프린터의 결함 유형 결정 방법 및 컴퓨터 판독 가능한 기록 매체
WO2019159324A1 (ja) * 2018-02-16 2019-08-22 パナソニックＩｐマネジメント株式会社 処理方法およびそれを利用した処理装置
US11151711B2 (en) * 2018-06-06 2021-10-19 Kla-Tencor Corporation Cross layer common-unique analysis for nuisance filtering
CN109001211A (zh) * 2018-06-08 2018-12-14 苏州赛克安信息技术有限公司 基于卷积神经网络的长输管道焊缝检测系统及方法
KR102745239B1 (ko) 2018-09-06 2024-12-20 삼성전자주식회사 컨볼루셔널 뉴럴 네트워크를 이용하는 컴퓨팅 장치 및 그 동작 방법
US11537687B2 (en) * 2018-11-19 2022-12-27 Groq, Inc. Spatial locality transform of matrices
US12340300B1 (en) 2018-09-14 2025-06-24 Groq, Inc. Streaming processor architecture
US11094053B2 (en) * 2018-10-08 2021-08-17 Kla Corporation Deep learning based adaptive regions of interest for critical dimension measurements of semiconductor substrates
JP7221644B2 (ja) * 2018-10-18 2023-02-14 株式会社日立製作所 機器故障診断支援システムおよび機器故障診断支援方法
CN109585325B (zh) * 2018-12-05 2021-02-02 上海华力集成电路制造有限公司 检测晶边洗边边界的方法
US11550309B2 (en) * 2019-01-08 2023-01-10 Kla Corporation Unsupervised defect segmentation
CN109919907A (zh) * 2019-01-23 2019-06-21 华灿光电（浙江）有限公司 发光二极管外延片缺陷检测的方法和装置
US10474543B1 (en) * 2019-01-28 2019-11-12 Stradivision, INC. Method and device for economizing computing resources to be used during a process of verification of convolutional parameters using test pattern to enhance fault tolerance and fluctuation robustness in extreme situations
TWI722383B (zh) * 2019-02-01 2021-03-21 國立中正大學 應用於深度學習之預特徵萃取方法
JP7395566B2 (ja) * 2019-04-02 2023-12-11 株式会社半導体エネルギー研究所 検査方法
DE102019207575A1 (de) * 2019-05-23 2020-11-26 Volkswagen Aktiengesellschaft Verfahren zum Beurteilen einer funktionsspezifischen Robustheit eines Neuronalen Netzes
CN110197259A (zh) * 2019-05-30 2019-09-03 浙江大学 基于小批量数据集与深度学习算法的晶圆缺陷检测方法
US11487998B2 (en) * 2019-06-17 2022-11-01 Qualcomm Incorporated Depth-first convolution in deep neural networks
TWI738009B (zh) * 2019-06-20 2021-09-01 和碩聯合科技股份有限公司 物件偵測系統及物件偵測方法
US20220253052A1 (en) * 2019-08-23 2022-08-11 Landmark Graphics Corporation Anomaly Detection using Hybrid Autoencoder and Gaussian Process Regression
JP7165633B2 (ja) * 2019-08-27 2022-11-04 株式会社日立ハイテク 荷電粒子ビーム制御装置
US11113827B2 (en) * 2019-09-23 2021-09-07 Kla Corporation Pattern-to-design alignment for one-dimensional unique structures
JP7344754B2 (ja) * 2019-10-23 2023-09-14 株式会社日本製鋼所 学習モデル生成方法、コンピュータプログラム、設定値決定装置、成形機及び成形装置システム
US11068752B2 (en) 2019-10-31 2021-07-20 General Electric Company Inspection systems and methods including image classification module
WO2021083608A1 (en) 2019-11-01 2021-05-06 Asml Netherlands B.V. Machine learning based image generation for model base alignments
JP2021077756A (ja) 2019-11-07 2021-05-20 キオクシア株式会社 半導体プロセス解析装置および半導体プロセス解析プログラム
KR102850134B1 (ko) * 2019-11-26 2025-08-26 삼성전자주식회사 생성적 적대망들에 기반하여 웨이퍼 맵을 생성하는 프로그램 코드를 저장하는 비일시적 컴퓨터 판독가능 매체 및 컴퓨팅 장치
CN111177970B (zh) * 2019-12-10 2021-11-19 浙江大学 基于高斯过程和卷积神经网络的多阶段半导体过程虚拟计量方法
WO2021120179A1 (zh) 2019-12-20 2021-06-24 京东方科技集团股份有限公司 产品制造消息处理方法、设备和计算机存储介质
US12014529B2 (en) 2020-01-21 2024-06-18 Samsung Electronics Co., Ltd. Image processing method and apparatus using neural network
US11961219B2 (en) 2020-02-27 2024-04-16 KLA Corp. Generative adversarial networks (GANs) for simulating specimen images
JP7262409B2 (ja) 2020-03-06 2023-04-21 株式会社日立ハイテク 試料観察システム及び画像処理方法
CA3178580A1 (en) 2020-05-14 2021-11-18 Eric FITERMAN Creating imagery for al model training in security screening
WO2021250884A1 (ja) * 2020-06-12 2021-12-16 株式会社日立ハイテク 欠陥検査のための方法、システム、及びコンピューター可読媒体
JP7442939B2 (ja) * 2020-07-02 2024-03-05 株式会社ディスコ ウエーハの検査方法
US20230259120A1 (en) * 2020-07-17 2023-08-17 Honeywell International Inc. Intelligent workflow engine for manufacturing process
CN114104328B (zh) * 2020-08-31 2023-10-17 中国航天科工飞航技术研究院（中国航天海鹰机电技术研究院） 基于深度迁移学习的飞行器状态监测方法
US11798828B2 (en) * 2020-09-04 2023-10-24 Kla Corporation Binning-enhanced defect detection method for three-dimensional wafer structures
CN112202736B (zh) * 2020-09-15 2021-07-06 浙江大学 基于统计学习和深度学习的通信网络异常分类方法
US20220092388A1 (en) * 2020-09-18 2022-03-24 The Boeing Company Machine learning network for screening quantum devices
WO2022074877A1 (ja) * 2020-10-08 2022-04-14 パナソニックＩｐマネジメント株式会社 処理方法およびそれを利用した処理装置
US12443840B2 (en) * 2020-10-09 2025-10-14 Kla Corporation Dynamic control of machine learning based measurement recipe optimization
US11822345B2 (en) * 2020-10-23 2023-11-21 Xerox Corporation Controlling an unmanned aerial vehicle by re-training a sub-optimal controller
WO2022088082A1 (zh) * 2020-10-30 2022-05-05 京东方科技集团股份有限公司 基于缺陷检测的任务处理方法、装置及设备及存储介质
US11639906B2 (en) * 2020-11-21 2023-05-02 Samsung Electronics Co., Ltd. Method and system for virtually executing an operation of an energy dispersive X-ray spectrometry (EDS) system in real-time production line
JP7101235B2 (ja) * 2020-12-17 2022-07-14 株式会社クボタ 検査装置及び検査方法
JP7101236B2 (ja) * 2020-12-17 2022-07-14 株式会社クボタ 検査装置及び検査方法
JP6961846B1 (ja) 2021-01-08 2021-11-05 レーザーテック株式会社 Ｅｕｖマスク検査装置、ｅｕｖマスク検査方法、ｅｕｖマスク検査プログラム及びｅｕｖマスク検査システム
WO2022169420A1 (en) * 2021-02-05 2022-08-11 Singapore University Of Technology And Design Anomaly detection system and method for an industrial control system
EP4047431B1 (de) * 2021-02-19 2025-11-19 FactoryPal GmbH Verfahren und vorrichtung zum automatisierten bestimmen einer optimierten prozesskonfiguration eines prozesses zur herstellung oder bearbeitung von produkten
JP7661721B2 (ja) * 2021-03-01 2025-04-15 東洋製罐株式会社 異常検知に関する方法、プログラム、装置及びシステム
TWI770922B (zh) 2021-03-31 2022-07-11 財團法人工業技術研究院 低精度神經網路的資料特徵擴增系統及方法
WO2022255518A1 (ko) * 2021-06-03 2022-12-08 주식회사 솔루션에이 딥러닝 신경망 모델을 이용한 검사대상 패널의 결함 판정장치
EP4371063A1 (en) * 2021-07-14 2024-05-22 Basf Se System for assessing the quality of a physical object
KR102404166B1 (ko) 2021-07-20 2022-06-02 국민대학교산학협력단 스타일 전이를 활용한 엑스레이 영상의 유체 탐지 방법 및 장치
KR102877633B1 (ko) 2021-09-01 2025-10-28 에스케이하이닉스 주식회사 반도체 웨이퍼의 불량 분석 방법 및 그 시스템
KR102354681B1 (ko) * 2021-11-08 2022-01-24 주식회사 테스트웍스 신경망 모델 기반의 이미지 증강 방법, 서버 및 컴퓨터 프로그램
US12111355B2 (en) 2021-11-22 2024-10-08 Onto Innovation Inc. Semiconductor substrate yield prediction based on spectra data from multiple substrate dies
CN114283412B (zh) * 2021-12-22 2025-09-19 上海蒙帕信息技术有限公司 一种数字仪表盘的读数识别方法与系统
CN116958561B (zh) * 2022-03-31 2026-04-07 富士通株式会社 检测异常对象的方法、装置和存储介质
US12332615B2 (en) * 2022-03-31 2025-06-17 Tyco Fire & Security Gmbh Building equipment control system with automated horizon selection
CN115060251B (zh) * 2022-04-28 2024-08-16 清华大学 地理电磁图像数据集的构建方法、装置和计算机设备
US12482091B2 (en) * 2022-08-10 2025-11-25 Kla Corporation Detecting defects on specimens
US20240126251A1 (en) * 2022-10-13 2024-04-18 Bingnan Wang System And Method For Motor Eccentricity Level Prediction Using Topological Data Analysis
US20240169514A1 (en) * 2022-11-21 2024-05-23 Onto Innovation Inc. Defect detection in manufactured articles using multi-channel images
CN117115178B (zh) * 2023-08-23 2024-05-14 国网四川省电力公司电力科学研究院 一种基于半参数共享的电力红外巡检图像分割、检测方法
WO2025188376A2 (en) * 2023-11-03 2025-09-12 Niricson, Inc. Platform for analyzing the condition of infrastructure using automated defect and change detection
US20260017838A1 (en) * 2024-07-10 2026-01-15 Applied Materials Israel Ltd. Automatic generation and planting of synthetic defects of interest and generation of synthetic fault images of semiconductor specimens

Family Cites Families (21)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2000232138A (ja) 1999-02-09 2000-08-22 Hitachi Ltd 半導体装置とそのマーク形成装置，その欠陥検査装置
JP4009409B2 (ja) * 1999-10-29 2007-11-14 株式会社日立製作所 パターン欠陥検査方法及びその装置
JP4542164B2 (ja) * 2008-03-18 2010-09-08 アドバンスド・マスク・インスペクション・テクノロジー株式会社 パターン検査装置、パターン検査方法及びプログラム
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
US8605275B2 (en) * 2009-01-26 2013-12-10 Kla-Tencor Corp. Detecting defects on a wafer
JP2012145664A (ja) * 2011-01-11 2012-08-02 Sony Corp 画像処理装置、撮像装置、画像処理方法およびプログラム。
JP5460662B2 (ja) * 2011-09-07 2014-04-02 株式会社日立ハイテクノロジーズ 領域決定装置、観察装置または検査装置、領域決定方法および領域決定方法を用いた観察方法または検査方法
US9171364B2 (en) * 2013-06-21 2015-10-27 Kla-Tencor Corp. Wafer inspection using free-form care areas
US9086639B2 (en) * 2013-09-12 2015-07-21 International Business Machines Corporation Fabrication of on-product aberration monitors with nanomachining
US10127652B2 (en) * 2014-02-06 2018-11-13 Kla-Tencor Corp. Defect detection and classification based on attributes determined from a standard reference image
US9535010B2 (en) * 2014-05-15 2017-01-03 Kla-Tencor Corp. Defect sampling for electron beam review based on defect attributes from optical inspection and optical review
WO2015189026A2 (en) 2014-06-10 2015-12-17 Asml Netherlands B.V. Computational wafer inspection
JP6337131B2 (ja) * 2014-09-30 2018-06-06 富士フイルム株式会社 赤外線撮像装置、固定パターンノイズ算出方法、及び固定パターンノイズ算出プログラム
US9395309B2 (en) 2014-10-15 2016-07-19 Exnodes Inc. Multiple angle computational wafer inspection
US20160110859A1 (en) 2014-10-17 2016-04-21 Macronix International Co., Ltd. Inspection method for contact by die to database
US10650508B2 (en) * 2014-12-03 2020-05-12 Kla-Tencor Corporation Automatic defect classification without sampling and feature selection
US9875536B2 (en) * 2015-03-31 2018-01-23 Kla-Tencor Corp. Sub-pixel and sub-resolution localization of defects on patterned wafers
CN105118044B (zh) * 2015-06-16 2017-11-07 华南理工大学 一种轮形铸造产品缺陷自动检测方法
CN105184309B (zh) * 2015-08-12 2018-11-16 西安电子科技大学 基于cnn和svm的极化sar图像分类
US9830526B1 (en) * 2016-05-26 2017-11-28 Adobe Systems Incorporated Generating image features based on robust feature-learning
US10223615B2 (en) * 2016-08-23 2019-03-05 Dongfang Jingyuan Electron Limited Learning based defect classification

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