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Accurate and Fast reconstruction of Porous Media from Extremely Limited
  Information Using Conditional Generative Adversarial Network

Accurate and Fast reconstruction of Porous Media from Extremely Limited Information Using Conditional Generative Adversarial Network

4 April 2019
Junxi Feng
Xiaohai He
Qizhi Teng
Chao Ren
Honggang Chen
Yang Li
    AI4CE3DVGAN
ArXiv (abs)PDFHTML

Papers citing "Accurate and Fast reconstruction of Porous Media from Extremely Limited Information Using Conditional Generative Adversarial Network"

2 / 2 papers shown
Title
Generating unrepresented proportions of geological facies using
  Generative Adversarial Networks
Generating unrepresented proportions of geological facies using Generative Adversarial Networks
A. Abdellatif
A. Elsheikh
G. Graham
Daniel Busby
Philippe Berthet
CVBMGANAI4CE
34
9
0
17 Mar 2022
DeePore: a deep learning workflow for rapid and comprehensive
  characterization of porous materials
DeePore: a deep learning workflow for rapid and comprehensive characterization of porous materials
A. Rabbani
M. Babaei
R. Shams
Ying Da Wang
Traiwit Chung
AI4CE
30
72
0
03 May 2020
1