38 citations · 48 across the 11 of their papers we have counts for
7 papers · 1 filter
Trust the Unreliability: Inward Backward Dynamic Unreliability Driven Coreset Selection for Medical Image Classification
Yan Liang, Ziyuan Yang, Zhuxin Lei +3
Efficiently managing and utilizing large-scale medical imaging datasets with limited resources presents significant challenges. While coreset selection helps reduce computational c…
One CT Unified Model Training Framework to Rule All Scanning Protocols
Fengzhi Xu, Ziyuan Yang, Zexin Lu +4
Non-ideal measurement computed tomography (NICT), which lowers radiation at the cost of image quality, is expanding the clinical use of CT. Although unified models have shown promi…
FedPalm: A General Federated Learning Framework for Closed- and Open-Set Palmprint Verification
Ziyuan Yang, Yingyu Chen, Chengrui Gao +3
Current deep learning (DL)-based palmprint verification models rely on centralized training with large datasets, which raises significant privacy concerns due to biometric data's s…
Double Banking on Knowledge: Customized Modulation and Prototypes for Multi-Modality Semi-supervised Medical Image Segmentation
Yingyu Chen, Ziyuan Yang, Ming Yan +4
Multi-modality (MM) semi-supervised learning (SSL) based medical image segmentation has recently gained increasing attention for its ability to utilize MM data and reduce reliance…
Trustworthy Hate Speech Detection Through Visual Augmentation
Ziyuan Yang, Ming Yan, Yingyu Chen +3
The surge of hate speech on social media platforms poses a significant challenge, with hate speech detection~(HSD) becoming increasingly critical. Current HSD methods focus on enri…
SynFacePAD 2023: Competition on Face Presentation Attack Detection Based on Privacy-aware Synthetic Training Data
Meiling Fang, Marco Huber, Julian Fierrez +21
This paper presents a summary of the Competition on Face Presentation Attack Detection Based on Privacy-aware Synthetic Training Data (SynFacePAD 2023) held at the 2023 Internation…
EVIL: Evidential Inference Learning for Trustworthy Semi-supervised Medical Image Segmentation
Yingyu Chen, Ziyuan Yang, Chenyu Shen +3
Recently, uncertainty-aware methods have attracted increasing attention in semi-supervised medical image segmentation. However, current methods usually suffer from the drawback tha…