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Xing Yao

13 papers hereh-index 677 citations18 works total

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

author position
  • first author2
  • middle author10

Across the 12 of 13 papers where every author was matched, so the position is known.

fields
  • cs.CV7
  • eess.IV6
same name
  • Xing Yao — 2 papers, h 3
  • Xing Yao — 1 paper, h 1
  • Xing Yao — 1 paper, h 1
  • Xing Yao — 1 paper, h 2
  • Xing Yao — 1 paper, h 0

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
20232025
most citedFalse Negative/Positive Control for SAM on Noisy Medical Images

5 citations · 9 across the 12 of their papers we have counts for

collaborators
Showing 2023 · cs.CVShow all

4 papers · 2 filters

cs.CV2023

MAP: Domain Generalization via Meta-Learning on Anatomy-Consistent Pseudo-Modalities

Dewei Hu, Hao Li, Han Liu +3

Deep models suffer from limited generalization capability to unseen domains, which has severely hindered their clinical applicability. Specifically for the retinal vessel segmentat…

cs.CV2023★ 5 cited

False Negative/Positive Control for SAM on Noisy Medical Images

Xing Yao, Han Liu, Dewei Hu +9

The Segment Anything Model (SAM) is a recently developed all-range foundation model for image segmentation. It can use sparse manual prompts such as bounding boxes to generate pixe…

cs.CV2023

VesselMorph: Domain-Generalized Retinal Vessel Segmentation via Shape-Aware Representation

Dewei Hu, Hao Li, Han Liu +3

Due to the absence of a single standardized imaging protocol, domain shift between data acquired from different sites is an inherent property of medical images and has become a maj…

cs.CV2023

COLosSAL: A Benchmark for Cold-start Active Learning for 3D Medical Image Segmentation

Han Liu, Hao Li, Xing Yao +6

Medical image segmentation is a critical task in medical image analysis. In recent years, deep learning based approaches have shown exceptional performance when trained on a fully-…

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