Results

eNauka >  Results >  Application of Machine Learning to Express Measurement Uncertainty
Title: Application of Machine Learning to Express Measurement Uncertainty
Authors: Vladimir Polužanski  ; Uroš Kovačević  ; Nebojša Bacanin  ; T. Rashid; S. Stojanović  ; Boško Nikolić  
Issue Date: 2022
Publication: Applied Sciences
ISSN: 2076-3417 Applied Sciences-Basel Search Idenfier
Type: Article
Collation: vol. 12 br. 17 str. 8581-8581
DOI: 10.3390/app12178581
WoS-ID: 000850942200001
Scopus-ID: 2-s2.0-85137884278
URI: http://zaposleni.etf.bg.ac.rs/rest/sciNaucniRezultati/oai/record/2/708631
https://enauka.gov.rs/handle/123456789/741322
URL: https://www.mdpi.com/2076-3417/12/17/8581
M-category: 
22M22

4
SCOPUSTM
2
OpenCitations
3
WEB OF SCIENCETM
Altmetric
Dimensions

Find the DOI

Unpaywall

Items in eNauka are protected by copyright, with all rights reserved, unless otherwise indicated.