Detailed study of spectral features obtained from LIBS and Raman spectroscopy

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26620%2F20%3APU137846" target="_blank" >RIV/00216305:26620/20:PU137846 - isvavai.cz</a>
Result on the web
<a href="https://www.scixconference.org/" target="_blank" >https://www.scixconference.org/</a>
DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Detailed study of spectral features obtained from LIBS and Raman spectroscopy
Original language description
Investigation of samples is getting complex when providing structural and chemical analysis. The chemical analysis itself may be obtained via the utilization of various techniques giving diverse, yet complementary information. Their combined utilization is not trivial when considering sample preparation, sampling, data collection, and processing. In our work, we focus on elaborate data processing to provide robust data analysis and not using machine learning tools as black boxes. This demands a straightforward connection of machine learning to the data sources (e.g., spectroscopy, plasma physics, analytical chemistry) for efficient feature extraction and visualization. We have selected a series of polymer materials characterized by complex spectra datasets obtained by using various spectroscopic methods (LIBS and Raman spectroscopy). We demonstrate a step-by-step algorithm for polymer classification using individual spectroscopic datasets as well as their combination. The robustness of our classificat
Czech name
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Czech description
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Project
<a href="/en/project/LQ1601" target="_blank" >LQ1601: CEITEC 2020</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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