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Jiayuan Wang

4 papers hereh-index 7319 citations10 works total

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

author position
  • first author1
  • middle author3

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CG2
  • cs.CV1
  • eess.IV1
same name
  • Jiayuan Wang — 7 papers, h 1
  • Jiayuan Wang — 4 papers, h 1
  • Jiayuan Wang — 3 papers, h 3
  • Jiayuan Wang — 1 paper, h 9
  • Jiayuan Wang — 1 paper, h 2
  • Jiayuan Wang — 1 paper, h 1

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

activity
20152022
most citedDC-cycleGAN: Bidirectional CT-to-MR Synthesis from Unpaired Data

65 citations · 99 across the 4 of their papers we have counts for

collaborators

4 papers

eess.IV2022★ 65 cited

DC-cycleGAN: Bidirectional CT-to-MR Synthesis from Unpaired Data

Jiayuan Wang, Q. M. Jonathan Wu, Farhad Pourpanah

Magnetic resonance (MR) and computer tomography (CT) images are two typical types of medical images that provide mutually-complementary information for accurate clinical diagnosis…

cs.CV2019★ 17 cited

Road Network Reconstruction from Satellite Images with Machine Learning Supported by Topological Methods

Tamal K. Dey, Jiayuan Wang, Yusu Wang

Automatic Extraction of road network from satellite images is a goal that can benefit and even enable new technologies. Methods that combine machine learning (ML) and computer visi…

cs.CG2018★ 16 cited

Graph Reconstruction by Discrete Morse Theory

Tamal K. Dey, Jiayuan Wang, Yusu Wang

Recovering hidden graph-like structures from potentially noisy data is a fundamental task in modern data analysis. Recently, a persistence-guided discrete Morse-based framework to…

cs.CG2015★ 1 cited

Declutter and Resample: Towards parameter free denoising

Mickaël Buchet, Tamal K. Dey, Jiayuan Wang +1

In many data analysis applications the following scenario is commonplace: we are given a point set that is supposed to sample a hidden ground truth K in a metric space, but it go…

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