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Daoqiang Zhang

4 papers hereh-index 211 citations15 works total

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

author position
  • middle author2
  • last author2

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

fields
  • cs.CV4
same name
  • Daoqiang Zhang — 7 papers, h 5
  • Daoqiang Zhang — 6 papers, h 8
  • Daoqiang Zhang — 4 papers, h 6
  • Daoqiang Zhang — 3 papers, h 0
  • Daoqiang Zhang — 3 papers, h 3
  • Daoqiang Zhang — 3 papers, h 3

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

collaborators

4 papers

cs.CV2026

CT-Conditioned Diffusion Prior with Physics-Constrained Sampling for PET Super-Resolution

Liutao Yang, Zi Wang, Peiyuan Jing +5

PET super-resolution is highly under-constrained because paired multi-resolution scans from the same subject are rarely available, and effective resolution is determined by scanner…

cs.CV2026

Advancing Cancer Prognosis with Hierarchical Fusion of Genomic, Proteomic and Pathology Imaging Data from a Systems Biology Perspective

Junjie Zhou, Bao Xue, Meiling Wang +2

To enhance the precision of cancer prognosis, recent research has increasingly focused on multimodal survival methods by integrating genomic data and histology images. However, cur…

cs.CV2025

MAPLE: Multi-scale Attribute-enhanced Prompt Learning for Few-shot Whole Slide Image Classification

Junjie Zhou, Wei Shao, Yagao Yue +4

Prompt learning has emerged as a promising paradigm for adapting pre-trained vision-language models (VLMs) to few-shot whole slide image (WSI) classification by aligning visual fea…

cs.CV2025

COME: Dual Structure-Semantic Learning with Collaborative MoE for Universal Lesion Detection Across Heterogeneous Ultrasound Datasets

Lingyu Chen, Yawen Zeng, Yue Wang +5

Conventional single-dataset training often fails with new data distributions, especially in ultrasound (US) image analysis due to limited data, acoustic shadows, and speckle noise.…

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