公开(公告)号：US20210103857A1

公开(公告)日：2021-04-08

申请号：US17064560

申请日：2020-10-06

Applicant: Coretronic Corporation

Inventor： Feng Wang ,  Yen-Chun Huang

IPC: G06N20/00 ,  G01J3/28

Abstract: The invention provides an automated model training method for training a pipeline for different spectrometers. The automated model training method includes: obtaining first spectral data corresponding to a first spectrometer, and second spectral data corresponding to a second spectrometer; and training the pipeline for the first spectrometer and the second spectrometer according to the first spectral data and the second spectral data, wherein the pipeline corresponds to at least one candidate recognition model. The invention also provides an automated model training device.

公开(公告)号：US11852532B2

公开(公告)日：2023-12-26

申请号：US17535691

申请日：2021-11-26

Applicant: Coretronic Corporation

Inventor： Feng Wang ,  Yen-Chun Huang ,  Kui-Ting Chen

IPC: G01J3/28 ,  G01J3/02

CPC classification number: G01J3/0275 ,  G01J2003/2836

Abstract: An electronic device and a method for spectral model explanation are provided. The method includes: obtaining first labeled spectral data; storing a plurality of pipelines, selecting a selected pipeline from the pipelines, and generating a first measurement result corresponding to the first labeled spectral data according to the selected pipeline; and determining an important wavelength range corresponding to the selected pipeline according to the first measurement result.

公开(公告)号：US20210103855A1

公开(公告)日：2021-04-08

申请号：US17037557

申请日：2020-09-29

Applicant: Coretronic Corporation

Inventor： Feng Wang ,  Yen-Chun Huang

IPC: G06N20/00 ,  G06N7/00 ,  G06K9/62 ,  G06F7/24 ,  G01N21/25

Abstract: The disclosure provides an automated model training method for a spectrometer, wherein the model training method is executed by a processor, and the model training method includes: obtaining spectral data; selecting at least one preprocessing model from one or a plurality of preprocessing models; selecting a first machine learning model from one or a plurality of machine learning models; establishing a pipeline corresponding to the at least one preprocessing model and the first machine learning model; and training an identification model corresponding to the pipeline according to the spectral data and the pipeline. The disclosure further provides a model training device and a spectrometer.

公开(公告)号：US20220170790A1

公开(公告)日：2022-06-02

申请号：US17535691

申请日：2021-11-26

Applicant: Coretronic Corporation

Inventor： Feng Wang ,  Yen-Chun Huang ,  Kui-Ting Chen

IPC: G01J3/02

Abstract: An electronic device and a method for spectral model explanation are provided. The method includes: obtaining first labeled spectral data; storing a plurality of pipelines, selecting a selected pipeline from the pipelines, and generating a first measurement result corresponding to the first labeled spectral data according to the selected pipeline; and determining an important wavelength range corresponding to the selected pipeline according to the first measurement result.

公开(公告)号：US20220163387A1

公开(公告)日：2022-05-26

申请号：US17533116

申请日：2021-11-23

Applicant: Coretronic Corporation

Inventor： Feng Wang ,  Yen-Chun Huang ,  Kui-Ting Chen

IPC: G01J3/28 ,  G06K9/62 ,  G06N20/00

Abstract: A method for optimizing an output result of a spectrometer and an electronic device using the method are provided. The method includes the following. First spectral data and second spectral data are obtained. A plurality of pipelines including a first pipeline and a second pipeline are obtained. The first pipeline is selected from the plurality of pipelines as a selected pipeline. The output result corresponding to the second spectral data is generated according to the selected pipeline. A performance of the first pipeline is calculated according to the first spectral data, and a first instruction is generated according to the performance. The selected pipeline is changed into the second pipeline according to the first instruction to update the output result.