CAOSP abstracts, Volume: 52, No.: 3, year: 2022

Author(s): Rabasovic, M.S.; Marinkovic, B.P.; Sevic, D.
Journal: Contributions of the Astronomical Observatory Skalnaté Pleso, vol. 52, no. 3, p. 126-131.
Date: 12/2022
Title: Analysis of laser induced plasma plume in atmosphere using deep learning
Keyword(s): Machine learning, Deep learning, Laser induced breakdown spectroscopy
Pages: 126 -- 131
DOI: https://doi.org/10.31577/caosp.2022.52.3.126
NASA ADS Abstract Service: 2022CoSka..52c.126R
Citation:
License: This work is licensed under a Creative Commons Attribution 4.0 International License

Abstract: The regression analysis of spectra of laser initiated electric discharge spark in atmosphere is presented here. Spectral images of optical emission of atmospheric plasma are obtained by a streak camera and integrated in time to obtain sample spectra of plasma with different apparent temperatures. We already have analyzed such spectra using principal component analysis and classification techniques. Now, we have advanced research through the ANN and deep learning technique. Namely, large set of measured spectra are used to train the artificial neural network to obtain the estimation of apparent plasma temperature. For machine learning approach to data analysis we use Solo+Mia software package (Version 9.0, Eigenvector Research Inc, USA).