Home ›
Entities
› academia
› Computed Tomography 3D Super-Resolution with Generative Adversarial Neural Networks: Implications on Unsaturated and Two-Phase Fluid Flow
Computed Tomography 3D Super-Resolution with Generative Adversarial Neural Networks: Implications on Unsaturated and Two-Phase Fluid Flow
Research article (Materials, 2020) · cited 44× · AI/ML
Computed Tomography 3D Super-Resolution with Generative Adversarial Neural Networks: Implications on Unsaturated and Two-Phase Fluid Flow
Summary
Computed Tomography 3D Super-Resolution with Generative Adversarial Neural Networks: Implications on Unsaturated and Two-Phase Fluid Flow is a scholarly article[1].
Key Facts
Computed Tomography 3D Super-Resolution with Generative Adversarial Neural Networks: Implications on Unsaturated and Two-Phase Fluid Flow's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Computed Tomography 3D Super-Resolution with Generative Adversarial Neural Networks: Implications on Unsaturated and Two-Phase Fluid Flow. Retrieved May 24, 2026, from https://4ort.xyz/entity/computed-tomography-3d-super-resolution-with-generative-adversarial-neural-networks-implications-on-unsaturated-and-two-
MLA“Computed Tomography 3D Super-Resolution with Generative Adversarial Neural Networks: Implications on Unsaturated and Two-Phase Fluid Flow.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/computed-tomography-3d-super-resolution-with-generative-adversarial-neural-networks-implications-on-unsaturated-and-two-.
BibTeX@misc{4ortxyz_computed-tomography-3d-super-resolution-with-generative-adversarial-neural-networks-implications-on-unsaturated-and-two-_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Computed Tomography 3D Super-Resolution with Generative Adversarial Neural Networks: Implications on Unsaturated and Two-Phase Fluid Flow}}, year = {2026}, url = {https://4ort.xyz/entity/computed-tomography-3d-super-resolution-with-generative-adversarial-neural-networks-implications-on-unsaturated-and-two-}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Computed Tomography 3D Super-Resolution with Generative Adversarial Neural Networks: Implications on Unsaturated and Two-Phase Fluid Flow — https://4ort.xyz/entity/computed-tomography-3d-super-resolution-with-generative-adversarial-neural-networks-implications-on-unsaturated-and-two- (retrieved 2026-05-24)
