MX2022008349A - Identificacion de falsos positivos reducidos para clasificacion espectroscopica. - Google Patents

Identificacion de falsos positivos reducidos para clasificacion espectroscopica.

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Publication number
MX2022008349A
MX2022008349A MX2022008349A MX2022008349A MX2022008349A MX 2022008349 A MX2022008349 A MX 2022008349A MX 2022008349 A MX2022008349 A MX 2022008349A MX 2022008349 A MX2022008349 A MX 2022008349A MX 2022008349 A MX2022008349 A MX 2022008349A
Authority
MX
Mexico
Prior art keywords
spectroscopic
classification model
false positive
information identifying
unknown sample
Prior art date
Application number
MX2022008349A
Other languages
English (en)
Inventor
Christopher G Pederson
Gunten Marc K Von
Lan Sun
Changmeng Hsiung
Original Assignee
Viavi Solutions Inc
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Publication date
Application filed by Viavi Solutions Inc filed Critical Viavi Solutions Inc
Publication of MX2022008349A publication Critical patent/MX2022008349A/es

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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00Pattern recognition
    • G06F18/20Analysing
    • G06F18/25Fusion techniques
    • G06F18/254Fusion techniques of classification results, e.g. of results related to same input data
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/31Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
    • G01N21/35Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01JMEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J3/00Spectrometry; Spectrophotometry; Monochromators; Measuring colours
    • G01J3/02Details
    • G01J3/10Arrangements of light sources specially adapted for spectrometry or colorimetry
    • G01J3/108Arrangements of light sources specially adapted for spectrometry or colorimetry for measurement in the infrared range
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/251Colorimeters; Construction thereof
    • G01N21/253Colorimeters; Construction thereof for batch operation, i.e. multisample apparatus
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/31Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
    • G01N21/35Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
    • G01N21/359Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using near infrared light
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84Systems specially adapted for particular applications
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00Pattern recognition
    • G06F18/20Analysing
    • G06F18/24Classification techniques
    • G06F18/241Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
    • G06F18/2411Classification 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
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00Pattern recognition
    • G06F18/20Analysing
    • G06F18/24Classification techniques
    • G06F18/243Classification techniques relating to the number of classes
    • G06F18/2433Single-class perspective, e.g. one-against-all classification; Novelty detection; Outlier detection
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00Machine learning
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00Machine learning
    • G06N20/10Machine learning using kernel methods, e.g. support vector machines [SVM]
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00Scenes; Scene-specific elements
    • G06V20/60Type of objects
    • G06V20/69Microscopic objects, e.g. biological cells or cellular parts
    • G06V20/698Matching; Classification
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16CCOMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
    • G16C20/00Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
    • G16C20/20Identification of molecular entities, parts thereof or of chemical compositions
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16CCOMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
    • G16C20/00Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
    • G16C20/70Machine learning, data mining or chemometrics
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2201/00Features of devices classified in G01N21/00
    • G01N2201/12Circuits of general importance; Signal processing
    • G01N2201/129Using chemometrical methods

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • General Physics & Mathematics (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Data Mining & Analysis (AREA)
  • Chemical & Material Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Evolutionary Computation (AREA)
  • Artificial Intelligence (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Immunology (AREA)
  • Pathology (AREA)
  • Analytical Chemistry (AREA)
  • Biochemistry (AREA)
  • General Engineering & Computer Science (AREA)
  • Software Systems (AREA)
  • Computing Systems (AREA)
  • Evolutionary Biology (AREA)
  • Medical Informatics (AREA)
  • Crystallography & Structural Chemistry (AREA)
  • Mathematical Physics (AREA)
  • Databases & Information Systems (AREA)
  • Multimedia (AREA)
  • Molecular Biology (AREA)
  • Biomedical Technology (AREA)
  • Investigating Or Analysing Materials By Optical Means (AREA)
  • Investigating, Analyzing Materials By Fluorescence Or Luminescence (AREA)
  • Spectrometry And Color Measurement (AREA)
  • Other Investigation Or Analysis Of Materials By Electrical Means (AREA)

Abstract

Un dispositivo puede recibir información que identifica resultados de un conjunto de mediciones espectroscópicas de un conjunto de entrenamiento de muestras conocidas y un conjunto de validación de muestras conocidas. El dispositivo puede generar un modelo de clasificación con base en la información que identifica los resultados del conjunto de mediciones espectroscópicas, en donde el modelo de clasificación incluye al menos una clase con respecto a un material de interés para una determinación espectroscópica, y en donde el modelo de clasificación incluye una clase sin coincidencias con respecto a al menos uno de al menos un material que no de interés o una medición espectroscópica de referencia. El dispositivo puede recibir información que identifica un resultado particular de una medición espectroscópica particular de una muestra desconocida. El dispositivo puede determinar si la muestra desconocida está incluida en la clase sin coincidencias utilizando el modelo de clasificación. El dispositivo puede proporcionar salida que indica si la muestra desconocida está incluida en la clase sin coincidencias.
MX2022008349A 2018-01-26 2019-01-10 Identificacion de falsos positivos reducidos para clasificacion espectroscopica. MX2022008349A (es)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US201862622637P 2018-01-26 2018-01-26
US16/130,732 US10810408B2 (en) 2018-01-26 2018-09-13 Reduced false positive identification for spectroscopic classification

Publications (1)

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MX2022008349A true MX2022008349A (es) 2022-08-08

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MX2019000411A MX2019000411A (es) 2018-01-26 2019-01-10 Identidificacion falsa positiva reducida para clasificacion espectroscopica.

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US (3) US10810408B2 (es)
EP (2) EP3518147A1 (es)
JP (3) JP6942741B2 (es)
KR (3) KR102338904B1 (es)
CN (2) CN113989603A (es)
CA (1) CA3029507A1 (es)
MX (2) MX2022008349A (es)
TW (3) TW202343352A (es)

Families Citing this family (17)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11009452B2 (en) 2018-01-26 2021-05-18 Viavi Solutions Inc. Reduced false positive identification for spectroscopic quantification
US11656174B2 (en) 2018-01-26 2023-05-23 Viavi Solutions Inc. Outlier detection for spectroscopic classification
US10810408B2 (en) 2018-01-26 2020-10-20 Viavi Solutions Inc. Reduced false positive identification for spectroscopic classification
US11223638B2 (en) * 2018-12-27 2022-01-11 Rapid7, Inc. Stable network user account classifier
JP6856103B2 (ja) * 2019-09-30 2021-04-07 株式会社三洋物産 遊技機
JP7353940B2 (ja) * 2019-11-26 2023-10-02 株式会社日立製作所 転移可能性判定装置、転移可能性判定方法、及び転移可能性判定プログラム
JP7418200B2 (ja) 2019-12-19 2024-01-19 キヤノン株式会社 識別装置、処理装置、処理方法、およびプログラム
JP7361594B2 (ja) * 2019-12-19 2023-10-16 キヤノン株式会社 識別装置、処理装置、処理方法、およびプログラム
CN113093967A (zh) * 2020-01-08 2021-07-09 富泰华工业(深圳)有限公司 数据生成方法、装置、计算机装置及存储介质
WO2021168611A1 (en) * 2020-02-24 2021-09-02 Yangtze Memory Technologies Co., Ltd. Systems and methods for semiconductor chip surface topography metrology
WO2021168613A1 (en) 2020-02-24 2021-09-02 Yangtze Memory Technologies Co., Ltd. Systems and methods for semiconductor chip surface topography metrology
WO2021168612A1 (en) 2020-02-24 2021-09-02 Yangtze Memory Technologies Co., Ltd. Systems and methods for semiconductor chip surface topography metrology
US11727089B2 (en) * 2020-09-08 2023-08-15 Nasdaq, Inc. Modular machine learning systems and methods
EP4033419A1 (en) * 2021-01-20 2022-07-27 Viavi Solutions Inc. Outlier detection for spectroscopic classification
TWI760206B (zh) * 2021-05-04 2022-04-01 行政院農業委員會農業藥物毒物試驗所 基於光譜圖辨識提供風險值的光學量測方法、光學量測系統、伺服端電腦裝置與客戶端電腦裝置
US20230038984A1 (en) * 2021-07-30 2023-02-09 Viavi Solutions Inc. Utilizing prediction thresholds to facilitate spectroscopic classification
CN114692719B (zh) * 2022-02-24 2023-04-07 电子科技大学 一种基于svm-Tradboost模型迁移的XRF小样本元素分类方法

Family Cites Families (42)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
FR2566543B1 (fr) 1984-06-20 1988-02-26 Commissariat Energie Atomique Dispositif optique a rendement de collection eleve et cytofluorimetre en faisant application
JP2922110B2 (ja) 1994-02-22 1999-07-19 株式会社エヌ・ティ・ティ・データ 物品同定システム
US7133710B2 (en) 2002-03-08 2006-11-07 Sensys Medical, Inc. Compact apparatus for noninvasive measurement of glucose through near-infrared spectroscopy
US6785638B2 (en) * 2001-08-06 2004-08-31 Timbre Technologies, Inc. Method and system of dynamic learning through a regression-based library generation process
AU2003258062A1 (en) 2002-08-05 2004-02-23 Infraredx, Inc. Near-infrared spectroscopic analysis of blood vessel walls
US7218395B2 (en) * 2003-04-16 2007-05-15 Optopo Inc. Rapid pharmaceutical identification and verification system
AU2005309338A1 (en) * 2004-11-29 2006-06-01 Scientific Analytics Systems Pty Ltd Modelling a phenomenon that has spectral data
EP1836600A4 (en) * 2004-11-29 2009-03-04 Scient Analytics Systems Pty L MODELING A PHENOMENON THAT HAS SPECTRAL DATA
WO2006135806A2 (en) * 2005-06-09 2006-12-21 Chemimage Corporation Forensic integrated search technology
WO2007105150A2 (en) 2006-03-10 2007-09-20 Koninklijke Philips Electronics, N.V. Methods and systems for identification of dna patterns through spectral analysis
US20110237446A1 (en) * 2006-06-09 2011-09-29 Chemlmage Corporation Detection of Pathogenic Microorganisms Using Fused Raman, SWIR and LIBS Sensor Data
US7990532B2 (en) * 2007-01-16 2011-08-02 Chemimage Corporation Method and apparatus for multimodal detection
EP1992939A1 (en) * 2007-05-16 2008-11-19 National University of Ireland, Galway A kernel-based method and apparatus for classifying materials or chemicals and for quantifying the properties of materials or chemicals in mixtures using spectroscopic data.
WO2009082418A2 (en) * 2007-10-12 2009-07-02 Real-Time Analyzers, Inc. Method and apparatus for determining properties of fuels
CN101504363A (zh) 2009-03-18 2009-08-12 哈尔滨商业大学 一种基于近红外光谱分析的食用油脂酸价检测方法
WO2011077765A1 (ja) 2009-12-25 2011-06-30 古河電気工業株式会社 検体識別分取装置および検体識別分取方法
US8859969B2 (en) 2012-03-27 2014-10-14 Innovative Science Tools, Inc. Optical analyzer for identification of materials using reflectance spectroscopy
EP2648133A1 (fr) * 2012-04-04 2013-10-09 Biomerieux Identification de microorganismes par spectrometrie et classification structurée
NL2009015C2 (en) * 2012-04-10 2013-10-15 Biosparq B V Method for classification of a sample on the basis of spectral data, method for creating a database and method for using this database, and corresponding computer program, data storage medium and system.
CN103364359A (zh) 2012-04-11 2013-10-23 天士力制药集团股份有限公司 Simca模式识别法在近红外光谱识别大黄药材中的应用
US10043264B2 (en) * 2012-04-19 2018-08-07 Applied Materials Israel Ltd. Integration of automatic and manual defect classification
US20130311136A1 (en) * 2012-05-18 2013-11-21 Mustard Tree Instruments, Llc Rule-Based Sample Verification and Chemical Monitoring Methodology
WO2014165331A1 (en) 2013-03-21 2014-10-09 Jds Uniphase Corporation Spectroscopic characterization of seafood
AU2014318499B2 (en) * 2013-09-16 2019-05-16 Biodesix, Inc Classifier generation method using combination of mini-classifiers with regularization and uses thereof
WO2015080001A1 (ja) 2013-11-27 2015-06-04 大日本印刷株式会社 培地情報登録システム、コロニー検出装置、プログラム及び衛生管理システム
CA2932399A1 (en) * 2013-12-02 2015-06-11 Qbase, LLC Method for disambiguating features in unstructured text
JP2017500577A (ja) * 2013-12-23 2017-01-05 サーモ サイエンティフィック ポータブル アナリティカル インスツルメンツ インコーポレイテッド フィールド使用分光装置の適応
WO2016054031A1 (en) 2014-10-02 2016-04-07 Biodesix, Inc. Predictive test for aggressiveness or indolence of prostate cancer from mass spectrometry of blood-based sample
JP6547275B2 (ja) * 2014-10-29 2019-07-24 株式会社リコー 情報処理システム、情報処理装置、情報処理方法、及びプログラム
US9824434B2 (en) 2015-08-18 2017-11-21 Industrial Technology Research Institute System and method for object recognition
EP3822977A1 (en) 2015-08-26 2021-05-19 Viavi Solutions Inc. Identification using spectroscopy
RU2018127709A (ru) 2016-01-22 2020-02-25 Отрэйсис, Инк. Системы и способы улучшения диагностики заболеваний
WO2017174580A1 (en) 2016-04-04 2017-10-12 Boehringer Ingelheim Rcv Gmbh & Co Kg Real time monitoring of product purification
EP3258285B1 (en) 2016-06-14 2020-10-21 Bruker BioSpin GmbH Method for predicting chemical shift values of nmr spin systems in a sample of a fluid class, in particular in a sample of a biofluid
US10444213B2 (en) * 2016-08-25 2019-10-15 Viavi Solutions Inc. Spectroscopic classification of conformance with dietary restrictions
CN106772417B (zh) * 2016-12-31 2017-11-14 华中科技大学 一种动目标多维度多尺度红外光谱特征测量方法及系统
US10936921B2 (en) 2017-06-15 2021-03-02 Spynsite Llc Machine learning and/or image processing for spectral object classification
CN107480690A (zh) * 2017-07-04 2017-12-15 中国科学院计算技术研究所 一种基于支持向量机的包含未知类别的多分类方法
CN107561024B (zh) 2017-07-17 2020-03-17 核工业北京地质研究院 一种适用于盐湖富铀水体的高光谱遥感识别方法
US10810408B2 (en) 2018-01-26 2020-10-20 Viavi Solutions Inc. Reduced false positive identification for spectroscopic classification
US11656174B2 (en) 2018-01-26 2023-05-23 Viavi Solutions Inc. Outlier detection for spectroscopic classification
US11009452B2 (en) 2018-01-26 2021-05-18 Viavi Solutions Inc. Reduced false positive identification for spectroscopic quantification

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TWI810013B (zh) 2023-07-21
CN113989603A (zh) 2022-01-28
JP2023088913A (ja) 2023-06-27
KR20230124871A (ko) 2023-08-28
TW202343352A (zh) 2023-11-01
TW202244826A (zh) 2022-11-16
CA3029507A1 (en) 2019-07-26
US20190236333A1 (en) 2019-08-01
US20230273122A1 (en) 2023-08-31
MX2019000411A (es) 2019-09-10
KR102338904B1 (ko) 2021-12-13
JP6942741B2 (ja) 2021-09-29
EP3518147A1 (en) 2019-07-31
TWI776010B (zh) 2022-09-01
US10810408B2 (en) 2020-10-20
US11656175B2 (en) 2023-05-23
EP4206653A1 (en) 2023-07-05
KR20210153579A (ko) 2021-12-17
US20210034838A1 (en) 2021-02-04
JP2019179023A (ja) 2019-10-17
CN110084261A (zh) 2019-08-02
KR102569560B1 (ko) 2023-08-22
JP2021192051A (ja) 2021-12-16
TW201933261A (zh) 2019-08-16
CN110084261B (zh) 2021-11-02
KR20190091205A (ko) 2019-08-05
JP7238056B2 (ja) 2023-03-13

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