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researcher

Min Zhu

4 papers hereh-index 3122 citations9 works total

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

author position
  • middle author4

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

fields
  • cs.CV3
  • eess.IV1
same name
  • Min Zhu — 8 papers, h 5
  • Min Zhu — 4 papers, h 10
  • Min Zhu — 4 papers, h 2
  • Min Zhu — 4 papers, h 5
  • Min Zhu — 4 papers, h 4
  • Min Zhu — 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

activity
20232026
most citedSA-Med2D-20M Dataset: Segment Anything in 2D Medical Imaging with 20 Million masks

14 citations · 14 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2026

MedP-CLIP: Medical CLIP with Region-Aware Prompt Integration

Jiahui Peng, He Yao, Jingwen Li +9

Contrastive Language-Image Pre-training (CLIP) has demonstrated outstanding performance in global image understanding and zero-shot transfer through large-scale text-image alignmen…

cs.CV2026

SegMoTE: Token-Level Mixture of Experts for Medical Image Segmentation

Yujie Lu, Jingwen Li, Sibo Ju +5

Medical image segmentation is vital for clinical diagnosis and quantitative analysis, yet remains challenging due to the heterogeneity of imaging modalities and the high cost of pi…

cs.CV2024

Interactive Medical Image Segmentation: A Benchmark Dataset and Baseline

Junlong Cheng, Bin Fu, Jin Ye +10

Interactive Medical Image Segmentation (IMIS) has long been constrained by the limited availability of large-scale, diverse, and densely annotated datasets, which hinders model gen…

eess.IV2023★ 14 cited

SA-Med2D-20M Dataset: Segment Anything in 2D Medical Imaging with 20 Million masks

Jin Ye, Junlong Cheng, Jianpin Chen +12

Segment Anything Model (SAM) has achieved impressive results for natural image segmentation with input prompts such as points and bounding boxes. Its success largely owes to massiv…

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