Enhancing images of shale formations by a hybrid stochastic and deep learning algorithm

S Kamrava, P Tahmasebi, M Sahimi - Neural Networks, 2019 - Elsevier
Accounting for the morphology of shale formations, which represent highly heterogeneous
porous media, is a difficult problem. Although two-or three-dimensional images of such …
被引用次数：90 相关文章

[引用][C] Enhancing images of shale formations by a hybrid stochastic and deep learning algorithm

S Kamrava, P Tahmasebi, M Sahimi - Neural Networks, 2019 - cir.nii.ac.jp
Enhancing images of shale formations by a hybrid stochastic and deep learning algorithm |
CiNii Research CiNii 国立情報学研究所 学術情報ナビゲータ[サイニィ] 詳細へ移動 検索フォーム …

Enhancing images of shale formations by a hybrid stochastic and deep learning algorithm

S Kamrava, P Tahmasebi… - Neural networks: the …, 2019 - pubmed.ncbi.nlm.nih.gov
Accounting for the morphology of shale formations, which represent highly heterogeneous
porous media, is a difficult problem. Although two-or three-dimensional images of such …

Enhancing images of shale formations by a hybrid stochastic and deep learning algorithm

S Kamrava, P Tahmasebi, M Sahimi - 2019 - dl.acm.org
Accounting for the morphology of shale formations, which represent highly heterogeneous
porous media, is a difficult problem. Although two-or three-dimensional images of such …

Enhancing images of shale formations by a hybrid stochastic and deep learning algorithm.

S Kamrava, P Tahmasebi, M Sahimi - Neural Networks: the Official …, 2019 - europepmc.org
Accounting for the morphology of shale formations, which represent highly heterogeneous
porous media, is a difficult problem. Although two-or three-dimensional images of such …