Detail publikace

Fast identification of biominerals by means of stand-off laser induced breakdown spectroscopy using linear discriminant analysis and artificial neural networks

Originální název

Fast identification of biominerals by means of stand-off laser induced breakdown spectroscopy using linear discriminant analysis and artificial neural networks

Anglický název

Fast identification of biominerals by means of stand-off laser induced breakdown spectroscopy using linear discriminant analysis and artificial neural networks

Jazyk

en

Originální abstrakt

The goal of this paper is to compare two selected statistical techniques used for identification of archeological materials merely on the base of their spectra obtained by stand-off laser-induced breakdown spectroscopy (stand-off LIBS). Data processing using linear discriminant analysis (LDA) and artificial neural networks (ANN) were applied on spectra of 18 different samples, some of them archeological and some recent, containing 7 types of material (i.e. shells, mortar, bricks, soil pellets, ceramic, teeth and bones). As the input data PCA scores were taken. The intended aim of this work is to create a database for simple and fast identification of archeological or paleontological materials in situ. This approach can speed up and simplify the sampling process during archeological excavations that nowadays tend to be quite damaging and timeconsuming.

Anglický abstrakt

The goal of this paper is to compare two selected statistical techniques used for identification of archeological materials merely on the base of their spectra obtained by stand-off laser-induced breakdown spectroscopy (stand-off LIBS). Data processing using linear discriminant analysis (LDA) and artificial neural networks (ANN) were applied on spectra of 18 different samples, some of them archeological and some recent, containing 7 types of material (i.e. shells, mortar, bricks, soil pellets, ceramic, teeth and bones). As the input data PCA scores were taken. The intended aim of this work is to create a database for simple and fast identification of archeological or paleontological materials in situ. This approach can speed up and simplify the sampling process during archeological excavations that nowadays tend to be quite damaging and timeconsuming.

Dokumenty

BibTex


@article{BUT92595,
  author="Gabriela {Vítková} and Karel {Novotný} and Jozef {Kaiser} and Lubomír {Prokeš} and Aleš {Hrdlička} and Jan {Novotný} and Radomír {Malina} and David {Procházka}",
  title="Fast identification of biominerals by means of stand-off laser induced breakdown spectroscopy using linear discriminant analysis and artificial neural networks",
  annote="The goal of this paper is to compare two selected statistical techniques used for identification of archeological materials merely on the base of their spectra obtained by stand-off laser-induced breakdown spectroscopy (stand-off LIBS). Data processing using linear discriminant analysis (LDA) and artificial neural networks (ANN) were applied on spectra of 18 different samples, some of them archeological and some recent, containing 7 types of material (i.e. shells, mortar, bricks, soil pellets, ceramic, teeth and bones). As the input data PCA scores were taken. The intended aim of this work is to create a database for simple and fast identification of archeological or paleontological materials in situ. This approach can speed up and simplify the sampling process during archeological excavations that nowadays tend to be quite damaging and timeconsuming.",
  chapter="92595",
  doi="10.1016/j.sab.2012.05.010",
  number="7",
  volume="73",
  year="2012",
  month="june",
  pages="1--6",
  type="journal article in Web of Science"
}