Benchmarking conventional and machine learning segmentation techniques for digital rock physics analysis of fractured rocks

Research article (Environmental Earth Sciences, 2022) · cited 64× · AI/ML
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Benchmarking conventional and machine learning segmentation techniques for digital rock physics analysis of fractured rocks

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Benchmarking conventional and machine learning segmentation techniques for digital rock physics analysis of fractured rocks is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Benchmarking conventional and machine learning segmentation techniques for digital rock physics analysis of fractured rocks. Retrieved May 24, 2026, from https://4ort.xyz/entity/benchmarking-conventional-and-machine-learning-segmentation-techniques-for-digital-rock-physics-analysis-of-fractured-ro
MLA “Benchmarking conventional and machine learning segmentation techniques for digital rock physics analysis of fractured rocks.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/benchmarking-conventional-and-machine-learning-segmentation-techniques-for-digital-rock-physics-analysis-of-fractured-ro.
BibTeX @misc{4ortxyz_benchmarking-conventional-and-machine-learning-segmentation-techniques-for-digital-rock-physics-analysis-of-fractured-ro_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Benchmarking conventional and machine learning segmentation techniques for digital rock physics analysis of fractured rocks}}, year = {2026}, url = {https://4ort.xyz/entity/benchmarking-conventional-and-machine-learning-segmentation-techniques-for-digital-rock-physics-analysis-of-fractured-ro}, note = {Accessed: 2026-05-24}}
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