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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
Pages to
4
Pages count
URL
https://www.nature.com/articles/s41597-020-0396-8
Full text in the Digital Library
http://hdl.handle.net/11012/188045
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" }