MX2022008349A - Identificacion de falsos positivos reducidos para clasificacion espectroscopica. - Google Patents
Identificacion de falsos positivos reducidos para clasificacion espectroscopica.Info
- 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
Links
- 238000013145 classification model Methods 0.000 abstract 4
- 238000005259 measurement Methods 0.000 abstract 4
- 238000010200 validation analysis Methods 0.000 abstract 1
Classifications
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- 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
- 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
- G01N21/31—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
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- 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
- 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
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- 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]
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- 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
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- 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)
- 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.
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 |
---|---|
MX2022008349A true MX2022008349A (es) | 2022-08-08 |
Family
ID=64949198
Family Applications (2)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
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. |
Family Applications After (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
MX2019000411A MX2019000411A (es) | 2018-01-26 | 2019-01-10 | Identidificacion falsa positiva reducida para clasificacion espectroscopica. |
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) | TW202343352A (es) |
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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 |
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JP6856103B2 (ja) * | 2019-09-30 | 2021-04-07 | 株式会社三洋物産 | 遊技機 |
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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 |
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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 |
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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 |
-
2018
- 2018-09-13 US US16/130,732 patent/US10810408B2/en active Active
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2019
- 2019-01-03 EP EP19150264.0A patent/EP3518147A1/en not_active Ceased
- 2019-01-03 EP EP23157642.2A patent/EP4206653A1/en active Pending
- 2019-01-09 TW TW112124935A patent/TW202343352A/zh unknown
- 2019-01-09 CA CA3029507A patent/CA3029507A1/en active Pending
- 2019-01-09 TW TW111129742A patent/TWI810013B/zh active
- 2019-01-09 TW TW108100900A patent/TWI776010B/zh active
- 2019-01-10 MX MX2022008349A patent/MX2022008349A/es unknown
- 2019-01-10 MX MX2019000411A patent/MX2019000411A/es unknown
- 2019-01-21 JP JP2019007899A patent/JP6942741B2/ja active Active
- 2019-01-21 CN CN202111346296.9A patent/CN113989603A/zh active Pending
- 2019-01-21 CN CN201910054785.3A patent/CN110084261B/zh active Active
- 2019-01-23 KR KR1020190008936A patent/KR102338904B1/ko active IP Right Grant
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2020
- 2020-10-16 US US17/072,437 patent/US11656175B2/en active Active
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2021
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2023
- 2023-03-01 JP JP2023031287A patent/JP2023088913A/ja active Pending
- 2023-05-04 US US18/312,241 patent/US20230273122A1/en active Pending
- 2023-08-17 KR KR1020230107648A patent/KR20230124871A/ko not_active Application Discontinuation
Also Published As
Publication number | Publication date |
---|---|
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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