Deep semi-supervised learning using generative adversarial networks for automated seismic facies classification of mass transport complex

Xu, Rachel; Puzyrev, Vladimir; Elders, Chris; Fathi Salmi, Ebrahim; Sellers, Ewan

doi:10.1016/j.cageo.2023.105450

Computers & Geosciences

2023

DOI: 10.1016/j.cageo.2023.105450

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Deep semi-supervised learning using generative adversarial networks for automated seismic facies classification of mass transport complex

Rachel Xu,

Vladimir Puzyrev,

Chris Elders

et al.

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Cited by 6 publications

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Deep semi-supervised learning using generative adversarial networks for automated seismic facies classification of mass transport complex

Cited by 6 publications

References 25 publications

Borehole lithology modelling with scarce labels by deep transductive learning

Borehole lithology modelling with scarce labels by deep transductive learning

Combining deep neural network and spatio-temporal clustering to automatically assess rockburst and seismic hazard – Case study from Marcel coal mine in Upper Silesian Basin, Poland

Research on elastic parameter inversion method based on seismic facies-controlled deep learning network

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