7 citations · 8 across the 10 of their papers we have counts for
6 papers · 1 filter
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…
Time Evidence Fusion Network: Multi-source View in Long-Term Time Series Forecasting
Tianxiang Zhan, Yuanpeng He, Yong Deng +3
In practical scenarios, time series forecasting necessitates not only accuracy but also efficiency. Consequently, the exploration of model architectures remains a perennially trend…
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…
EPL: Evidential Prototype Learning for Semi-supervised Medical Image Segmentation
Yuanpeng He
Although current semi-supervised medical segmentation methods can achieve decent performance, they are still affected by the uncertainty in unlabeled data and model predictions, an…