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BUDAY, J.; CEMPÍREK, J.; VÝRAVSKÝ, J.; POŘÍZKA, P.; KAISER, J.
Original Title
Robust Mineralogy Analysis Utilizing Laser-Induced Breakdown Spectroscopy and Dispersive X-Ray Spectroscopy
English Title
Type
Paper in proceedings (conference paper)
Original Abstract
In this work, we focused on the analysis of large-scale geological samples combining LIBS and EDX. To use the LIBS for mineral identification, the k-means clustering method was utilized on the hyperspectral cube generated for each analyzed sample. As this method is in the category of unsupervised machine learning, we used the reference information from the EDX to specify the minerals within the sample.
English abstract
Keywords
LIBS, EDX, mineralogy, spectroscopy, clustering
Key words in English
Authors
RIV year
2025
Released
23.08.2024
ISBN
979-8-3503-6925-0
Book
2024 IEEE Sensors Applications Symposium (SAS)
2766-3078
Periodical
State
United States of America
Pages count
5
URL
https://ieeexplore.ieee.org/document/10636561
BibTex
@inproceedings{BUT189398, author="Jakub {Buday} and Jan {Cempírek} and Jakub {Výravský} and Pavel {Pořízka} and Jozef {Kaiser}", title="Robust Mineralogy Analysis Utilizing Laser-Induced Breakdown Spectroscopy and Dispersive X-Ray Spectroscopy", booktitle="2024 IEEE Sensors Applications Symposium (SAS)", year="2024", journal="2024 IEEE Sensors Applications Symposium (SAS)", pages="5", doi="10.1109/SAS60918.2024.10636561", isbn="979-8-3503-6925-0", issn="2766-3078", url="https://ieeexplore.ieee.org/document/10636561" }