7 citations · 8 across the 10 of their papers we have counts for
7 papers · 1 filter
Co-Evidential Fusion with Information Volume for Medical Image Segmentation
Yuanpeng He, Lijian Li, Tianxiang Zhan +3
Although existing semi-supervised image segmentation methods have achieved good performance, they cannot effectively utilize multiple sources of voxel-level uncertainty for targete…
Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation
Lijian Li, Yuanpeng He, Chi-Man Pun
Recently, prototype learning has emerged in semi-supervised medical image segmentation and achieved remarkable performance. However, the scarcity of labeled data limits the express…
Residual Feature-Reutilization Inception Network for Image Classification
Yuanpeng He, Wenjie Song, Lijian Li +2
Capturing feature information effectively is of great importance in the field of computer vision. With the development of convolutional neural networks (CNNs), concepts like residu…
Generalized Uncertainty-Based Evidential Fusion with Hybrid Multi-Head Attention for Weak-Supervised Temporal Action Localization
Yuanpeng He, Lijian Li, Tianxiang Zhan +2
Weakly supervised temporal action localization (WS-TAL) is a task of targeting at localizing complete action instances and categorizing them with video-level labels. Action-backgro…
Towards Realistic Long-tailed Semi-supervised Learning in an Open World
Yuanpeng He, Lijian Li
Open-world long-tailed semi-supervised learning (OLSSL) has increasingly attracted attention. However, existing OLSSL algorithms generally assume that the distributions between kno…
Uncertainty-aware Evidential Fusion-based Learning for Semi-supervised Medical Image Segmentation
Yuanpeng He, Lijian Li
Although the existing uncertainty-based semi-supervised medical segmentation methods have achieved excellent performance, they usually only consider a single uncertainty evaluation…