Home ›
Entities
› academia
› Assessing the fidelity of neural network-based segmentation of soil XCT images based on pore-scale modelling of saturated flow properties
Assessing the fidelity of neural network-based segmentation of soil XCT images based on pore-scale modelling of saturated flow properties
Research article (Soil and Tillage Research, 2021) · cited 46× · AI/ML
Assessing the fidelity of neural network-based segmentation of soil XCT images based on pore-scale modelling of saturated flow properties
Summary
Assessing the fidelity of neural network-based segmentation of soil XCT images based on pore-scale modelling of saturated flow properties is a scholarly article[1].
Key Facts
Assessing the fidelity of neural network-based segmentation of soil XCT images based on pore-scale modelling of saturated flow properties'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). Assessing the fidelity of neural network-based segmentation of soil XCT images based on pore-scale modelling of saturated flow properties. Retrieved May 24, 2026, from https://4ort.xyz/entity/assessing-the-fidelity-of-neural-network-based-segmentation-of-soil-xct-images-based-on-pore-scale-modelling-of-saturate
MLA“Assessing the fidelity of neural network-based segmentation of soil XCT images based on pore-scale modelling of saturated flow properties.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/assessing-the-fidelity-of-neural-network-based-segmentation-of-soil-xct-images-based-on-pore-scale-modelling-of-saturate.
BibTeX@misc{4ortxyz_assessing-the-fidelity-of-neural-network-based-segmentation-of-soil-xct-images-based-on-pore-scale-modelling-of-saturate_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Assessing the fidelity of neural network-based segmentation of soil XCT images based on pore-scale modelling of saturated flow properties}}, year = {2026}, url = {https://4ort.xyz/entity/assessing-the-fidelity-of-neural-network-based-segmentation-of-soil-xct-images-based-on-pore-scale-modelling-of-saturate}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Assessing the fidelity of neural network-based segmentation of soil XCT images based on pore-scale modelling of saturated flow properties — https://4ort.xyz/entity/assessing-the-fidelity-of-neural-network-based-segmentation-of-soil-xct-images-based-on-pore-scale-modelling-of-saturate (retrieved 2026-05-24)
