Corrigendum to “Deep-learning-based workflow for boundary and small target segmentation in digital rock images using UNet++ and IK-EBM” [215 (2022) 110596](S0920410522004715)(10.1016/j.petrol.2022.110596)
Publication
, Journal Article
Wang, H; Dalton, L; Fan, M; Guo, R; McClure, J; Crandall, D; Chen, C
Published in: Geoenergy Science and Engineering
February 1, 2023
Corresponding author: Cheng Chenff Department of Civil, Environmental and Ocean Engineering, Stevens Institute of Technology, Hoboken, NJ, 07030, USA. The authors regret: In the published paper, the affiliation for the corresponding author missed the university name (Stevens Institute of Technology). The correct affiliation should be: f Department of Civil, Environmental and Ocean Engineering, Stevens Institute of Technology, Hoboken, NJ, 07030, USA. The authors would like to apologise for any inconvenience caused.
Duke Scholars
Published In
Geoenergy Science and Engineering
DOI
EISSN
2949-8910
Publication Date
February 1, 2023
Volume
221
Citation
APA
Chicago
ICMJE
MLA
NLM
Wang, H., Dalton, L., Fan, M., Guo, R., McClure, J., Crandall, D., & Chen, C. (2023). Corrigendum to “Deep-learning-based workflow for boundary and small target segmentation in digital rock images using UNet++ and IK-EBM” [215 (2022) 110596](S0920410522004715)(10.1016/j.petrol.2022.110596). Geoenergy Science and Engineering, 221. https://doi.org/10.1016/j.petrol.2022.111306
Wang, H., L. Dalton, M. Fan, R. Guo, J. McClure, D. Crandall, and C. Chen. “Corrigendum to “Deep-learning-based workflow for boundary and small target segmentation in digital rock images using UNet++ and IK-EBM” [215 (2022) 110596](S0920410522004715)(10.1016/j.petrol.2022.110596).” Geoenergy Science and Engineering 221 (February 1, 2023). https://doi.org/10.1016/j.petrol.2022.111306.
Wang H, Dalton L, Fan M, Guo R, McClure J, Crandall D, et al. Corrigendum to “Deep-learning-based workflow for boundary and small target segmentation in digital rock images using UNet++ and IK-EBM” [215 (2022) 110596](S0920410522004715)(10.1016/j.petrol.2022.110596). Geoenergy Science and Engineering. 2023 Feb 1;221.
Wang, H., et al. “Corrigendum to “Deep-learning-based workflow for boundary and small target segmentation in digital rock images using UNet++ and IK-EBM” [215 (2022) 110596](S0920410522004715)(10.1016/j.petrol.2022.110596).” Geoenergy Science and Engineering, vol. 221, Feb. 2023. Scopus, doi:10.1016/j.petrol.2022.111306.
Wang H, Dalton L, Fan M, Guo R, McClure J, Crandall D, Chen C. Corrigendum to “Deep-learning-based workflow for boundary and small target segmentation in digital rock images using UNet++ and IK-EBM” [215 (2022) 110596](S0920410522004715)(10.1016/j.petrol.2022.110596). Geoenergy Science and Engineering. 2023 Feb 1;221.
Published In
Geoenergy Science and Engineering
DOI
EISSN
2949-8910
Publication Date
February 1, 2023
Volume
221