PaperMetrixEvidence-aware discovery
TR
Interface language English EN العربية AR Türkçe TR
Create account
Researcher profile

Huazhu Fu

6 papers in the PaperMetrix corpus

Publications

Papers by this author

  1. Reliable Federated Disentangling Network for Non-IID Domain Feature

    2023 · arXiv (Cornell University)

    Federated learning (FL), as an effective decentralized distributed learning approach, enables multiple institutions to jointly train a model without sharing their local data. However, the domain feature shift caused by different acquisition devices/clients substantially degrades …

  2. DiffMIC: Dual-Guidance Diffusion Network for Medical Image Classification

    2023 · arXiv (Cornell University)

    Diffusion Probabilistic Models have recently shown remarkable performance in generative image modeling, attracting significant attention in the computer vision community. However, while a substantial amount of diffusion-based research has focused on generative tasks, few studies …

  3. Frequency-mixed Single-source Domain Generalization for Medical Image Segmentation

    2023 · arXiv (Cornell University)

    The annotation scarcity of medical image segmentation poses challenges in collecting sufficient training data for deep learning models. Specifically, models trained on limited data may not generalize well to other unseen data domains, resulting in …

  4. An Aggregation-Free Federated Learning for Tackling Data Heterogeneity

    2024 · arXiv (Cornell University)

    The performance of Federated Learning (FL) hinges on the effectiveness of utilizing knowledge from distributed datasets. Traditional FL methods adopt an aggregate-then-adapt framework, where clients update local models based on a global model aggregated by …

  5. VSR-Net: Vessel-Like Structure Rehabilitation Network With Graph Clustering

    2025 · IEEE Transactions on Image Processing

    The morphologies of vessel-like structures, such as blood vessels and nerve fibres, play significant roles in disease diagnosis, e.g., Parkinson's disease. Although deep network-based refinement segmentation and topology-preserving segmentation methods recently have achieved promising results …

  6. UniVRSE: Unified Vision-conditioned Response Semantic Entropy for Hallucination Detection in Medical Vision-Language Models

    2025 · arXiv (Cornell University)

    Vision-language models (VLMs) have great potential for medical image understanding, particularly in Visual Report Generation (VRG) and Visual Question Answering (VQA), but they may generate hallucinated responses that contradict visual evidence, limiting clinical deployment. Although …