Epistemic Uncertainty and Model Transparency in Rock Facies Classification Using Monte Carlo Dropout Deep Learning

Although Deep Learning (DL) architectures have been used as efficient prediction tools in a variety of domains, they frequently do not care about the uncertainty in the predictions. This may prevent them from being used in practical applications. In seismic reservoir characterisation, predicting fac...

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Bibliografiske detaljer

Principais autores:	Touhid Mohammad Hossain, Maman Hermana, Said Jadid Abdulkadir
Format:	Artigo
Sprog:	Inglês
Udgivet:	IEEE 2023-01-01
Serier:	IEEE Access
Fag:	Uncertainty facies classification Monte Carlo dropout deep learning
Online adgang:	https://ieeexplore.ieee.org/document/10225733/
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