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Jun Gao

3 papers hereh-index 334 citations4 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2
  • last author1

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.CV3
same name
  • Jun Gao — 42 papers, h 25
  • Jun Gao — 27 papers, h 50
  • Jun Gao — 18 papers, h 9
  • Jun Gao — 17 papers, h 21
  • Jun Gao — 12 papers, h 4
  • Jun Gao — 12 papers, h 5

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedEnhancing Rock Image Segmentation in Digital Rock Physics: A Fusion of Generative AI and State-of-the-Art Neural Networks

8 citations · 15 across the 3 of their papers we have counts for

collaborators
Showing cs.CVShow all

3 papers · 1 filter

cs.CV2026

Physics-Consistent Diffusion for Efficient Fluid Super-Resolution via Multiscale Residual Correction

Zhihao Li, Shengwei Dong, Chuang Yi +5

Existing image SR and generic diffusion models transfer poorly to fluid SR: they are sampling-intensive, ignore physical constraints, and often yield spectral mismatch and spurious…

cs.CV2023★ 7 cited

Zero-Shot Digital Rock Image Segmentation with a Fine-Tuned Segment Anything Model

Zhaoyang Ma, Xupeng He, Shuyu Sun +3

Accurate image segmentation is crucial in reservoir modelling and material characterization, enhancing oil and gas extraction efficiency through detailed reservoir models. This pre…

cs.CV2023★ 8 cited

Enhancing Rock Image Segmentation in Digital Rock Physics: A Fusion of Generative AI and State-of-the-Art Neural Networks

Zhaoyang Ma, Xupeng He, Hyung Kwak +3

In digital rock physics, analysing microstructures from CT and SEM scans is crucial for estimating properties like porosity and pore connectivity. Traditional segmentation methods…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.