2 citations · 4 across the 8 of their papers we have counts for
9 papers
Learning Label-Efficient Interpretable Medical Image Diagnosis via Semi-supervised Hypergraph Concept Bottleneck Model
Yijun Yang, Ruiqiang Xiao, Lijie Hu +4
Deep learning has revolutionized medical image analysis, delivering exceptional diagnostic accuracy across diverse applications. Yet, the lack of interpretability in its decision-m…
EchoPilot: Training-Free Ultrasound Video Segmentation via Scale-Space Semantic Prompting and Reliability-Gated Memory
Ruiqiang Xiao, Zhaohu Xing, Yijun Yang +4
Ultrasound video segmentation is clinically valuable yet difficult due to speckle noise, weak boundaries, and rapid anatomical deformation. Recent promptable foundation models enab…
OsmT: Bridging OpenStreetMap Queries and Natural Language with Open-source Tag-aware Language Models
Zhuoyue Wan, Wentao Hu, Chen Jason Zhang +5
Bridging natural language and structured query languages is a long-standing challenge in the database community. While recent advances in language models have shown promise in this…
HRVVS: A High-resolution Video Vasculature Segmentation Network via Hierarchical Autoregressive Residual Priors
Xincheng Yao, Yijun Yang, Kangwei Guo +5
The segmentation of the hepatic vasculature in surgical videos holds substantial clinical significance in the context of hepatectomy procedures. However, owing to the dearth of an…
DRIVE: Dual-Robustness via Information Variability and Entropic Consistency in Source-Free Unsupervised Domain Adaptation
Ruiqiang Xiao, Songning Lai, Yijun Yang +3
Adapting machine learning models to new domains without labeled data, especially when source data is inaccessible, is a critical challenge in applications like medical imaging, aut…
Maintaining Informative Coherence: Migrating Hallucinations in Large Language Models via Absorbing Markov Chains
Jiemin Wu, Songning Lai, Ruiqiang Xiao +3
Large Language Models (LLMs) are powerful tools for text generation, translation, and summarization, but they often suffer from hallucinations-instances where they fail to maintain…
IRFusionFormer: Enhancing Pavement Crack Segmentation with RGB-T Fusion and Topological-Based Loss
Ruiqiang Xiao, Xiaohu Chen
Crack segmentation is crucial in civil engineering, particularly for assessing pavement integrity and ensuring the durability of infrastructure. While deep learning has advanced RG…
MatchSeg: Towards Better Segmentation via Reference Image Matching
Jiayu Huo, Ruiqiang Xiao, Haotian Zheng +3
Recently, automated medical image segmentation methods based on deep learning have achieved great success. However, they heavily rely on large annotated datasets, which are costly…
YOLOv5s-GTB: light-weighted and improved YOLOv5s for bridge crack detection
Xiao Ruiqiang
In response to the situation that the conventional bridge crack manual detection method has a large amount of human and material resources wasted, this study is aimed to propose a…