Publication detail

Benchmark classification dataset for laser-induced breakdown spectroscopy

KÉPEŠ, E. VRÁBEL, J. STŘÍTEŽSKÁ, S. POŘÍZKA, P. KAISER, J.

Original Title

Benchmark classification dataset for laser-induced breakdown spectroscopy

Type

journal article in Scopus

Language

English

Original Abstract

In this work, we present an extensive dataset of laser-induced breakdown spectroscopy (LIBS) spectra for the pre-training and evaluation of LIBS classification models. LIBS is a well-established spectroscopic method for in-situ and industrial applications, where LIBS is primarily applied for clustering and classification tasks. As such, our dataset is aimed at helping with the development and testing of classification and clustering methodologies. Moreover, the dataset could be used to pre-train classification models for applications where the amount of available data is limited. The dataset consists of LIBS spectra of 138 soil samples belonging to 12 distinct classes. The spectra were acquired with a state-of-the-art LIBS system. Lastly, the composition of each sample is also provided, including estimated uncertainties.

Keywords

laser-induced breakdown spectroscpoy, soil samples, benchmark, classification

Authors

KÉPEŠ, E.; VRÁBEL, J.; STŘÍTEŽSKÁ, S.; POŘÍZKA, P.; KAISER, J.

Released

13. 2. 2020

Publisher

Springer Nature

ISBN

2052-4463

Periodical

Scientific data

Year of study

7

Number

1

State

United Kingdom of Great Britain and Northern Ireland

Pages from

1

Pages to

4

Pages count

4

URL

Full text in the Digital Library

BibTex

@article{BUT161721,
  author="Erik {Képeš} and Jakub {Vrábel} and Sára {Střítežská} and Pavel {Pořízka} and Jozef {Kaiser}",
  title="Benchmark classification dataset for laser-induced breakdown
spectroscopy",
  journal="Scientific data",
  year="2020",
  volume="7",
  number="1",
  pages="1--4",
  doi="10.1038/s41597-020-0396-8",
  issn="2052-4463",
  url="https://www.nature.com/articles/s41597-020-0396-8"
}