49 citations · 66 across the 6 of their papers we have counts for
6 papers
Weakly Semi-supervised Whole Slide Image Classification by Two-level Cross Consistency Supervision
Linhao Qu, Shiman Li, Xiaoyuan Luo +4
Computer-aided Whole Slide Image (WSI) classification has the potential to enhance the accuracy and efficiency of clinical pathological diagnosis. It is commonly formulated as a Mu…
FAST: A Dual-tier Few-Shot Learning Paradigm for Whole Slide Image Classification
Kexue Fu, Xiaoyuan Luo, Linhao Qu +5
The expensive fine-grained annotation and data scarcity have become the primary obstacles for the widespread adoption of deep learning-based Whole Slide Images (WSI) classification…
Rethinking Multiple Instance Learning: Developing an Instance-Level Classifier via Weakly-Supervised Self-Training
Yingfan Ma, Xiaoyuan Luo, Mingzhi Yuan +2
Multiple instance learning (MIL) problem is currently solved from either bag-classification or instance-classification perspective, both of which ignore important information conta…
Knowledge Extraction and Distillation from Large-Scale Image-Text Colonoscopy Records Leveraging Large Language and Vision Models
Shuo Wang, Yan Zhu, Xiaoyuan Luo +8
The development of artificial intelligence systems for colonoscopy analysis often necessitates expert-annotated image datasets. However, limitations in dataset size and diversity i…
The Rise of AI Language Pathologists: Exploring Two-level Prompt Learning for Few-shot Weakly-supervised Whole Slide Image Classification
Linhao Qu, Xiaoyuan Luo, Kexue Fu +2
This paper introduces the novel concept of few-shot weakly supervised learning for pathology Whole Slide Image (WSI) classification, denoted as FSWC. A solution is proposed based o…
Robust Point Cloud Registration Framework Based on Deep Graph Matching(TPAMI Version)
Kexue Fu, Jiazheng Luo, Xiaoyuan Luo +3
3D point cloud registration is a fundamental problem in computer vision and robotics. Recently, learning-based point cloud registration methods have made great progress. However, t…