MX2019000411A - Identidificacion falsa positiva reducida para clasificacion espectroscopica. - Google Patents

Identidificacion falsa positiva reducida para clasificacion espectroscopica.

Info

Publication number
MX2019000411A
MX2019000411A MX2019000411A MX2019000411A MX2019000411A MX 2019000411 A MX2019000411 A MX 2019000411A MX 2019000411 A MX2019000411 A MX 2019000411A MX 2019000411 A MX2019000411 A MX 2019000411A MX 2019000411 A MX2019000411 A MX 2019000411A
Authority
MX
Mexico
Prior art keywords
spectroscopic
classification model
false positive
information identifying
unknown sample
Prior art date
Application number
MX2019000411A
Other languages
English (en)
Inventor
Hsiung Changmeng
G Pederson Christopher
K Von Gunten Marc
Sun Lan
Original Assignee
Viavi Solutions Inc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Viavi Solutions Inc filed Critical Viavi Solutions Inc
Publication of MX2019000411A publication Critical patent/MX2019000411A/es

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Classifications

    • 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
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
    • G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/25—Fusion techniques
    • G06F18/254—Fusion techniques of classification results, e.g. of results related to same input data
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
    • G01J3/02—Details
    • G01J3/10—Arrangements of light sources specially adapted for spectrometry or colorimetry
    • G01J3/108—Arrangements of light sources specially adapted for spectrometry or colorimetry for measurement in the infrared range
    • 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
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • 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
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/251—Colorimeters; Construction thereof
    • G01N21/253—Colorimeters; Construction thereof for batch operation, i.e. multisample apparatus
    • 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
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
    • G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
    • G01N21/359—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using near infrared light
    • 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
    • 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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/24—Classification techniques
    • G06F18/243—Classification techniques relating to the number of classes
    • G06F18/2433—Single-class perspective, e.g. one-against-all classification; Novelty detection; Outlier detection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • 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]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/60—Type of objects
    • G06V20/69—Microscopic objects, e.g. biological cells or cellular parts
    • G06V20/698—Matching; Classification
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16C—COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
    • G16C20/00—Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
    • G16C20/20—Identification of molecular entities, parts thereof or of chemical compositions
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16C—COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
    • G16C20/00—Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
    • G16C20/70—Machine learning, data mining or chemometrics
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2201/00—Features of devices classified in G01N21/00
    • G01N2201/12—Circuits of general importance; Signal processing
    • G01N2201/129—Using chemometrical methods

Landscapes

  • 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)
  • Analytical Chemistry (AREA)
  • Pathology (AREA)
  • Immunology (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)
  • Biomedical Technology (AREA)
  • Molecular Biology (AREA)
  • Multimedia (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.
MX2019000411A 2018-01-26 2019-01-10 Identidificacion falsa positiva reducida para clasificacion espectroscopica. MX2019000411A (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)

Publication Number Publication Date
MX2019000411A true MX2019000411A (es) 2019-09-10

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MX2022008349A MX2022008349A (es) 2018-01-26 2019-01-10 Identificacion de falsos positivos reducidos para clasificacion espectroscopica.
MX2019000411A MX2019000411A (es) 2018-01-26 2019-01-10 Identidificacion falsa positiva reducida para clasificacion espectroscopica.

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Country Status (8)

Country Link
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) TWI776010B (es)

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Publication number Publication date
US20230273122A1 (en) 2023-08-31
TWI810013B (zh) 2023-07-21
JP7238056B2 (ja) 2023-03-13
TW201933261A (zh) 2019-08-16
US11656175B2 (en) 2023-05-23
TW202244826A (zh) 2022-11-16
CN110084261B (zh) 2021-11-02
US10810408B2 (en) 2020-10-20
MX2022008349A (es) 2022-08-08
KR102569560B1 (ko) 2023-08-22
JP2021192051A (ja) 2021-12-16
KR20210153579A (ko) 2021-12-17
JP2023088913A (ja) 2023-06-27
JP2019179023A (ja) 2019-10-17
KR20230124871A (ko) 2023-08-28
TW202343352A (zh) 2023-11-01
KR20190091205A (ko) 2019-08-05
US20190236333A1 (en) 2019-08-01
KR102338904B1 (ko) 2021-12-13
TWI776010B (zh) 2022-09-01
EP3518147A1 (en) 2019-07-31
CA3029507A1 (en) 2019-07-26
CN110084261A (zh) 2019-08-02
JP6942741B2 (ja) 2021-09-29
US20210034838A1 (en) 2021-02-04
CN113989603A (zh) 2022-01-28
EP4206653A1 (en) 2023-07-05

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