Quantitative analysis modeling for the ChemCam spectral data based on laser-induced breakdown spectroscopy using convolutional neural network-Reference-Cited by-同舟云学术

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Quantitative analysis modeling for the ChemCam spectral data based on laser-induced breakdown spectroscopy using convolutional neural network

Published:2020-08-25 Issue:11 Volume:22 Page:115502
ISSN:1009-0630
Container-title:Plasma Science and Technology
language:
Short-container-title:Plasma Sci. Technol.

Author:

CAO Xueqiang,ZHANG Li,WU Zhongchen,LING Zongcheng,LI Jialun,GUO Kaichen

Funder

Natural Science Foundation of Shandong Province

National Natural Science Foundation of China

China National Space Administration

Major Research Project of Shandong province

Publisher

IOP Publishing

Subject

Condensed Matter Physics

Link

https://iopscience.iop.org/article/10.1088/2058-6272/aba5f6/pdf

Reference32 articles.

1. Quantitative Analysis of Cerium-Gallium Alloys Using a Hand-Held Laser Induced Breakdown Spectroscopy Device

2. Monitoring Uranium, Hydrogen, and Lithium and Their Isotopes Using a Compact Laser-Induced Breakdown Spectroscopy (LIBS) Probe and High-Resolution Spectrometer

3. Detection of uranyl fluoride and sand surface contamination on metal substrates by hand-held laser-induced breakdown spectroscopy

4. Characterization of Hydrogen in Basaltic Materials With Laser‐Induced Breakdown Spectroscopy ( LIBS ) for Application to MSL ChemCam Data

5. ChemCam activities and discoveries during the nominal mission of the Mars Science Laboratory in Gale crater, Mars

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