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Yi Zhang

13 papers hereh-index 11378 citations32 works total

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

author position
  • last author13

Across the 13 of 13 papers where every author was matched, so the position is known.

fields
  • cs.CV7
  • cs.CR4
  • cs.IR1
  • eess.IV1
same name
  • Yi Zhang — 41 papers, h 22
  • Yi Zhang — 38 papers
  • Yi Zhang — 35 papers, h 37
  • Yi Zhang — 33 papers, h 9
  • Yi Zhang — 23 papers, h 11
  • Yi Zhang — 22 papers, h 18

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
20232026
most citedA Dual-Level Cancelable Framework for Palmprint Verification and Hack-Proof Data Storage

12 citations · 15 across the 13 of their papers we have counts for

collaborators
Showing 2023Show all

4 papers · 1 filter

cs.CV2023

Energizing Federated Learning via Filter-Aware Attention

Ziyuan Yang, Zerui Shao, Huijie Huangfu +5

Federated learning (FL) is a promising distributed paradigm, eliminating the need for data sharing but facing challenges from data heterogeneity. Personalized parameter generation…

cs.CR2023

Privacy-Preserving Encrypted Low-Dose CT Denoising

Ziyuan Yang, Huijie Huangfu, Maosong Ran +3

Deep learning (DL) has made significant advancements in tomographic imaging, particularly in low-dose computed tomography (LDCT) denoising. A recent trend involves servers training…

cs.CV2023★ 2 cited

Physics-Driven Spectrum-Consistent Federated Learning for Palmprint Verification

Ziyuan Yang, Andrew Beng Jin Teoh, Bob Zhang +2

Palmprint as biometrics has gained increasing attention recently due to its discriminative ability and robustness. However, existing methods mainly improve palmprint verification w…

cs.CV2023

EVIL: Evidential Inference Learning for Trustworthy Semi-supervised Medical Image Segmentation

Yingyu Chen, Ziyuan Yang, Chenyu Shen +3

Recently, uncertainty-aware methods have attracted increasing attention in semi-supervised medical image segmentation. However, current methods usually suffer from the drawback tha…

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