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Artificial Neural Networks for Classification

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26620%2F22%3APU145851" target="_blank" >RIV/00216305:26620/22:PU145851 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.wiley.com/en-it/Chemometrics+and+Numerical+Methods+in+LIBS-p-9781119759584" target="_blank" >https://www.wiley.com/en-it/Chemometrics+and+Numerical+Methods+in+LIBS-p-9781119759584</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1002/9781119759614.ch9" target="_blank" >10.1002/9781119759614.ch9</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Artificial Neural Networks for Classification

  • Original language description

    Laser‐induced plasma emission spectra contain vast amounts of information. Yet, the discovery of appropriate patterns in laser‐induced breakdown spectra is paramount to reliably performing both quantitative and qualitative analysis. This chapter provides a brief introduction of artificial neural network (ANN) classification models, which have recently become a fundamental part of most pattern recognition toolboxes. The working principles of ANNs are discussed along with the most frequently used architecture types. Special attention is given to the training process of ANNs with the aim of aiding the reader's troubleshooting capabilities. Moreover, some of the potential perils of ANN models are presented. Namely, the risk of overtraining is addressed extensively while providing several potential ailments. Lastly, a comprehensive overview of the applications of ANNs for the classification of LIBS spectra is provided and a few exemplary use‐cases of ANN classifiers are discussed in detail.

  • Czech name

  • Czech description

Classification

  • Type

    C - Chapter in a specialist book

  • CEP classification

  • OECD FORD branch

    10406 - Analytical chemistry

Result continuities

  • Project

    <a href="/en/project/EF19_073%2F0016948" target="_blank" >EF19_073/0016948: Quality internal grants at BUT</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2022

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Book/collection name

    Chemometrics and Numerical Methods in LIBS

  • ISBN

    978-1-119-75958-4

  • Number of pages of the result

    28

  • Pages from-to

    213-240

  • Number of pages of the book

    384

  • Publisher name

    Neuveden

  • Place of publication

    Neuveden

  • UT code for WoS chapter