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researcher

Can Zhao

3 papers here

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

author position
  • middle author3

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

fields
  • cs.LG2
  • eess.IV1
ORCID 0000-0002-6939-359X
same name
  • Can Zhao — 6 papers, h 21
  • Can Zhao — 5 papers, h 15
  • Can Zhao — 2 papers
  • Can Zhao — 1 paper
  • Can Zhao — 1 paper
  • Can Zhao — 1 paper, h 6

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 citedGenerative AI for Medical Imaging: extending the MONAI Framework

41 citations · 45 across the 3 of their papers we have counts for

collaborators

3 papers

eess.IV2023★ 41 cited

Generative AI for Medical Imaging: extending the MONAI Framework

Walter H. L. Pinaya, Mark S. Graham, Eric Kerfoot +21

Recent advances in generative AI have brought incredible breakthroughs in several areas, including medical imaging. These generative models have tremendous potential not only to he…

cs.LG2023

Communication-Efficient Vertical Federated Learning with Limited Overlapping Samples

Jingwei Sun, Ziyue Xu, Dong Yang +6

Federated learning is a popular collaborative learning approach that enables clients to train a global model without sharing their local data. Vertical federated learning (VFL) dea…

cs.LG2023★ 4 cited

Fair Federated Medical Image Segmentation via Client Contribution Estimation

Meirui Jiang, Holger R Roth, Wenqi Li +6

How to ensure fairness is an important topic in federated learning (FL). Recent studies have investigated how to reward clients based on their contribution (collaboration fairness)…

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