1 citations · 2 across the 4 of their papers we have counts for
4 papers
Modeling the Label Distributions for Weakly-Supervised Semantic Segmentation
Linshan Wu, Zhun Zhong, Jiayi Ma +4
Weakly-Supervised Semantic Segmentation (WSSS) aims to train segmentation models by weak labels, which is receiving significant attention due to its low annotation cost. Existing a…
VoCo: A Simple-yet-Effective Volume Contrastive Learning Framework for 3D Medical Image Analysis
Linshan Wu, Jiaxin Zhuang, Hao Chen
Self-Supervised Learning (SSL) has demonstrated promising results in 3D medical image analysis. However, the lack of high-level semantics in pre-training still heavily hinders the…
Deep Covariance Alignment for Domain Adaptive Remote Sensing Image Segmentation
Linshan Wu, Ming Lu, Leyuan Fang
Unsupervised domain adaptive (UDA) image segmentation has recently gained increasing attention, aiming to improve the generalization capability for transferring knowledge from the…
Iterative Semi-Supervised Learning for Abdominal Organs and Tumor Segmentation
Jiaxin Zhuang, Luyang Luo, Zhixuan Chen +1
Deep-learning (DL) based methods are playing an important role in the task of abdominal organs and tumors segmentation in CT scans. However, the large requirements of annotated dat…