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researcher

Shen Zhao

4 papers hereh-index 684 citations12 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
  • Shen Zhao — 4 papers, h 4
  • Shen Zhao — 2 papers, h 10
  • Shen Zhao — 2 papers, h 7
  • Shen Zhao — 1 paper, h 0
  • Shen Zhao — 1 paper, h 1
  • Shen Zhao — 1 paper, h 23

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

Anatomy-Aware Text-Visual Fusion with Dual-Perspective Prompts for Fine-Grained Lumbar Spine Segmentation

Sheng Lian, Jianlong Cai, Dengfeng Pan +5

Accurate lumbar spine segmentation is crucial for diagnosing spinal disorders. Existing methods typically use coarse-grained segmentation strategies that lack the fine detail neede…

cs.CV2026

Unified Medical Image Segmentation with State Space Modeling Snake

Ruicheng Zhang, Haowei Guo, Kanghui Tian +4

Unified Medical Image Segmentation (UMIS) is critical for comprehensive anatomical assessment but faces challenges due to multi-scale structural heterogeneity. Conventional pixel-b…

cs.CV2025

GAMED-Snake: Gradient-aware Adaptive Momentum Evolution Deep Snake Model for Multi-organ Segmentation

Ruicheng Zhang, Haowei Guo, Zeyu Zhang +2

Multi-organ segmentation is a critical yet challenging task due to complex anatomical backgrounds, blurred boundaries, and diverse morphologies. This study introduces the Gradient-…

cs.CV2025

How to Efficiently Annotate Images for Best-Performing Deep Learning Based Segmentation Models: An Empirical Study with Weak and Noisy Annotations and Segment Anything Model

Yixin Zhang, Shen Zhao, Hanxue Gu +1

Deep neural networks (DNNs) have demonstrated exceptional performance across various image segmentation tasks. However, the process of preparing datasets for training segmentation…

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