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Yang Zhang

10 papers hereh-index 151.6k citations30 works total

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

author position
  • middle author10

Across the 10 of 10 papers where every author was matched, so the position is known.

fields
  • eess.IV5
  • cs.CV4
  • cs.LG1
same name
  • Yang Zhang — 50 papers, h 15
  • Yang Zhang — 37 papers, h 19
  • Yang Zhang — 36 papers, h 18
  • Yang Zhang — 35 papers, h 85
  • Yang Zhang — 28 papers, h 42
  • Yang Zhang — 24 papers, h 11

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
20192024
most citedModality-aware Mutual Learning for Multi-modal Medical Image Segmentation

10 citations · 20 across the 7 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2024

DomainVerse: A Benchmark Towards Real-World Distribution Shifts For Tuning-Free Adaptive Domain Generalization

Feng Hou, Jin Yuan, Ying Yang +7

Traditional cross-domain tasks, including domain adaptation and domain generalization, rely heavily on training model by source domain data. With the recent advance of vision-langu…

cs.CV2023

Epistemic Graph: A Plug-And-Play Module For Hybrid Representation Learning

Jin Yuan, Yang Zhang, Yangzhou Du +4

In recent years, deep models have achieved remarkable success in various vision tasks. However, their performance heavily relies on large training datasets. In contrast, humans exh…

cs.CV2021★ 1 cited

TumorCP: A Simple but Effective Object-Level Data Augmentation for Tumor Segmentation

Jiawei Yang, Yao Zhang, Yuan Liang +3

Deep learning models are notoriously data-hungry. Thus, there is an urging need for data-efficient techniques in medical image analysis, where well-annotated data are costly and ti…

cs.CV2020

Double-Uncertainty Weighted Method for Semi-supervised Learning

Yixin Wang, Yao Zhang, Jiang Tian +4

Though deep learning has achieved advanced performance recently, it remains a challenging task in the field of medical imaging, as obtaining reliable labeled training data is time-…

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