Publication detail

Robust Mineralogy Analysis Utilizing Laser-Induced Breakdown Spectroscopy and Dispersive X-Ray Spectroscopy

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

Type

conference paper

Language

English

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.

Keywords

LIBS, EDX, mineralogy, spectroscopy, clustering

Authors

BUDAY, J.; CEMPÍREK, J.; VÝRAVSKÝ, J.; POŘÍZKA, P.; KAISER, J.

Released

23. 8. 2024

ISBN

979-8-3503-6925-0

Book

2024 IEEE Sensors Applications Symposium (SAS)

ISBN

2766-3078

Periodical

2024 IEEE Sensors Applications Symposium (SAS)

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"
}