A transferred multitask regularization convolutional neural network (TrMR-CNN) for laser-induced breakdown spectroscopy quantitative analysis-Reference-Cited by-同舟云学术

A transferred multitask regularization convolutional neural network (TrMR-CNN) for laser-induced breakdown spectroscopy quantitative analysis

Published:2022 Issue:10 Volume:37 Page:2059-2068
ISSN:0267-9477
Container-title:Journal of Analytical Atomic Spectrometry
language:en
Short-container-title:J. Anal. At. Spectrom.

Author:

Cui Jiacheng¹^ORCID,Song Weiran¹^ORCID,Hou Zongyu¹²^ORCID,Gu Weilun¹^ORCID,Wang Zhe¹²^ORCID

Affiliation:

1. State Key Lab of Power Systems, International Joint Laboratory on Low Carbon Clean Energy Innovation, Department of Energy and Power Engineering, Tsinghua University, Beijing, 100084, China

2. Shanxi Research Institute for Clean Energy, Tsinghua University, Taiyuan, 030032, China

Abstract

A quantification method combining transfer learning, a convolutional neural network and multitask regularization to improve prediction accuracy and model robustness on limited data.

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

ShanXi Science and Technology Department

Publisher

Royal Society of Chemistry (RSC)

Subject

Spectroscopy,Analytical Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2022/JA/D2JA00182A

Reference32 articles.

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