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Xiangfeng Wang

34 papers hereh-index 211.7k citations104 works total

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

author position
  • middle author19
  • last author14

Across the 33 of 34 papers where every author was matched, so the position is known.

fields
  • cs.LG14
  • cs.AI6
  • cs.CV4
  • cs.MA2
  • cs.RO2
  • cs.CL1
same name
  • Xiangfeng Wang — 11 papers, h 3
  • Xiangfeng Wang — 9 papers, h 8
  • Xiangfeng Wang — 6 papers
  • Xiangfeng Wang — 5 papers
  • Xiangfeng Wang — 5 papers, h 4
  • Xiangfeng Wang — 3 papers, h 20

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
20182026
most citedFDA3 : Federated Defense Against Adversarial Attacks for Cloud-Based IIoT Applications

66 citations · 83 across the 21 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2024

Masked Autoencoders are Parameter-Efficient Federated Continual Learners

Yuchen He, Xiangfeng Wang

Federated learning is a specific distributed learning paradigm in which a central server aggregates updates from multiple clients' local models, thereby enabling the server to lear…

cs.CV2024

Interactive 3D Medical Image Segmentation with SAM 2

Chuyun Shen, Wenhao Li, Yuhang Shi +1

Interactive medical image segmentation (IMIS) has shown significant potential in enhancing segmentation accuracy by integrating iterative feedback from medical professionals. Howev…

cs.CV2023

Temporally-Extended Prompts Optimization for SAM in Interactive Medical Image Segmentation

Chuyun Shen, Wenhao Li, Ya Zhang +1

The Segmentation Anything Model (SAM) has recently emerged as a foundation model for addressing image segmentation. Owing to the intrinsic complexity of medical images and the high…

cs.CV2019

Iteratively-Refined Interactive 3D Medical Image Segmentation with Multi-Agent Reinforcement Learning

Xuan Liao, Wenhao Li, Qisen Xu +5

Existing automatic 3D image segmentation methods usually fail to meet the clinic use. Many studies have explored an interactive strategy to improve the image segmentation performan…

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