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Machine learning in radioactive nuclides identification
Title Machine learning in radioactive nuclides identification Author Krammer Peter 1984- SAVINFO - Ústav informatiky SAV SCOPUS RID ORCID Co-authors Hluchý Ladislav 1952- SAVINFO - Ústav informatiky SAV SCOPUS RID ORCID Bartok Juraj Source document / Szakál Anikó SISY 2013 : IEEE 11th International Symposium on Intelligent Systems and Informatics : proceedings. P. 57-61. - : IEEE Hungary Section, 2013 ; IEEE International Symposium on Intelligent Systems and Informatics SISY 2013 Language eng - English Country HU - Hungary Document kind rozpis článkov z periodík (rzb) Citations FJELDSTED, A. - BEVINS, J. - HOLLAND, D. - LINTEREUR, A. The effect of input features on advanced gammaray spectra analysis. In Proceedings of the INMM & ESARDA Joint Virtual Annual Meeting. 2021, pp. 1-10. https://resources.inmm.org/sites/default/files/2021-09/a552.pdf LI, Linxiang - HUANG, Guangwei - XI, Shanxue - WANG, Zungang - ZHOU, Chunzhi. Application of fuzzy probability factor superposition algorithm in nuclide identification. In JOURNAL OF RADIOANALYTICAL AND NUCLEAR CHEMISTRY, 2022, vol. 331, no. 5, pp. 2261-2271. ISSN 0236-5731. Dostupné na: https://doi.org/10.1007/s10967-022-08318-w. KUSUMA, Gina - KUSUMA, Sastra Wijaya - SUSILA, I. Putu. Radionuclide Identification in Open Environment Based on CsI(Na) Scintillation Detector Using Machine Learning Methods. In Proceedings 2023 10th International Conference on Computer, Control, Informatics and its Applications: Exploring the Power of Data: Leveraging Information to Drive Digital Innovation, IC3INA 2023, 2023-01-01, pp. 238-243. Dostupné na: https://doi.org/10.1109/IC3INA60834.2023.10285806. Category ADMB - Scientific papers in foreign non-impacted journals registered in Web of Sciences or Scopus Category of document (from 2022) V3 - Vedecký výstup publikačnej činnosti z časopisu Type of document článok Year 2013 Registered in SCOPUS DOI 10.1109/SISY.2013.6662617 
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