Corrigendum to “An end-to-end approach to predict physical properties of heterogeneous porous media: Coupling deep learning and physics-based features” [Fuel 352 (2023) 128753] (Fuel (2023) 352, (S0016236123013662), (10.1016/j.fuel.2023.128753))

Yuqi Wu, Senyou An*, Pejman Tahmasebi, Keyu Liu, Chengyan Lin, Serveh Kamrava, Chang Liu, Chenyang Yu, Tao Zhang, Shuyu Sun, Samuel Krevor, Vahid Niasar

*Corresponding author for this work

Research output: Contribution to journalComment/debatepeer-review

Abstract

In this corrigendum the authors have removed an extra caption in Figure 10 in the above cited paper. Unfortunately, one of the captions was not removed when a revision was implemented on this figure during the review process. The caption of this figure should have read as: Figure 10. (a) Comparison of 2D original LR and HR-CycleGAN images, illustrating that the latter can better capture fine-scale structures of the samples; (b) Comparison of 3D original LR, HR-Bicubic, and HR-CycleGAN images, demonstrating that the HR-CycleGAN images can contain much finer details compared with other images. The authors would like to apologize for any inconvenience caused.

Original languageEnglish (US)
Article number131358
JournalFuel
Volume364
DOIs
StatePublished - May 15 2024

Bibliographical note

Publisher Copyright:
© 2024 Elsevier Ltd

ASJC Scopus subject areas

  • General Chemical Engineering
  • Fuel Technology
  • Energy Engineering and Power Technology
  • Organic Chemistry

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