activity
20212023
most citedMulti-modal Contrastive Representation Learning for Entity Alignment

26 citations · 64 across the 14 of their papers we have counts for

collaborators

36 papers

cs.LG2024120 cited

Semi-supervised Credit Card Fraud Detection via Attribute-Driven Graph Representation

Sheng Xiang, Mingzhi Zhu, Dawei Cheng +5

Credit card fraud incurs a considerable cost for both cardholders and issuing banks. Contemporary methods apply machine learning-based classifiers to detect fraudulent behavior fro…

cs.CV2024

Unlocking the Potential of Weakly Labeled Data: A Co-Evolutionary Learning Framework for Abnormality Detection and Report Generation

Jinghan Sun, Dong Wei, Zhe Xu +7

Anatomical abnormality detection and report generation of chest X-ray (CXR) are two essential tasks in clinical practice. The former aims at localizing and characterizing cardiopul…

cs.CV202423 cited

Learning Spectral-Decomposed Tokens for Domain Generalized Semantic Segmentation

Jingjun Yi, Qi Bi, Hao Zheng +5

The rapid development of Vision Foundation Model (VFM) brings inherent out-domain generalization for a variety of down-stream tasks. Among them, domain generalized semantic segment…

eess.IV20245 cited

QUBIQ: Uncertainty Quantification for Biomedical Image Segmentation Challenge

Hongwei Bran Li, Fernando Navarro, Ivan Ezhov +77

Uncertainty in medical image segmentation tasks, especially inter-rater variability, arising from differences in interpretations and annotations by various experts, presents a sign…

eess.IV2024

MoME: Mixture of Multimodal Experts for Cancer Survival Prediction

Conghao Xiong, Hao Chen, Hao Zheng +4

Survival analysis, as a challenging task, requires integrating Whole Slide Images (WSIs) and genomic data for comprehensive decision-making. There are two main challenges in this t…

cs.CV2024

Prototype Correlation Matching and Class-Relation Reasoning for Few-Shot Medical Image Segmentation

Yumin Zhang, Hongliu Li, Yajun Gao +3

Few-shot medical image segmentation has achieved great progress in improving accuracy and efficiency of medical analysis in the biomedical imaging field. However, most existing met…