6 papers · 1 filter
Targeted Downstream-Agnostic Attack
Zhuxin Lei, Ziyuan Yang, Yi Zhang
Recently, pre-trained encoders have gained widespread use due to their strong capability in representation extraction. However, they are vulnerable to downstream-agnostic attacks (…
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…
Low-Level Dataset Distillation for Medical Image Enhancement
Fengzhi Xu, Ziyuan Yang, Mengyu Sun +2
Medical image enhancement is clinically valuable, but existing methods require large-scale datasets to learn complex pixel-level mappings. However, the substantial training and sto…
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…