1 citations · 2 across the 4 of their papers we have counts for
4 papers
AGLP: A Graph Learning Perspective for Semi-supervised Domain Adaptation
Houcheng Su, Mengzhu Wang, Jiao Li +3
In semi-supervised domain adaptation (SSDA), the model aims to leverage partially labeled target domain data along with a large amount of labeled source domain data to enhance its…
GraphCL: Graph-based Clustering for Semi-Supervised Medical Image Segmentation
Mengzhu Wang, Jiao Li, Houcheng Su +3
Semi-supervised learning (SSL) has made notable advancements in medical image segmentation (MIS), particularly in scenarios with limited labeled data and significantly enhancing da…
DiM: -Divergence Minimization Guided Sharpness-Aware Optimization for Semi-supervised Medical Image Segmentation
Bingli Wang, Houcheng Su, Nan Yin +2
As a technique to alleviate the pressure of data annotation, semi-supervised learning (SSL) has attracted widespread attention. In the specific domain of medical image segmentation…
Graph based Label Enhancement for Multi-instance Multi-label learning
Houcheng Su, Jintao Huang, Daixian Liu +3
Multi-instance multi-label (MIML) learning is widely applicated in numerous domains, such as the image classification where one image contains multiple instances correlated with mu…