12 citations · 15 across the 13 of their papers we have counts for
13 papers
PRISM: Refracting the Entangled User Behavior Space for E-Commerce Search
Haoqian Zhang, Ziyuan Yang, Yi Zhang
E-commerce search systems rely on modeling user behavior to estimate item relevance and user preference, which are typically assumed to be stable and independently learnable signal…
Asymmetric Invertible Threat: Learning Reversible Privacy Defense for Face Recognition
Jiabei Zhang, Ziyuan Yang, Andrew Beng Jin Teoh +1
Face Recognition systems are widely deployed in real-world applications, but they also raise privacy concerns due to unauthorized collection and misuse of facial data. Existing adv…
PalmBridge: A Plug-and-Play Feature Alignment Framework for Open-Set Palmprint Verification
Chenke Zhang, Ziyuan Yang, Licheng Yan +4
Palmprint recognition is widely used in biometric systems, yet real-world performance often degrades due to feature distribution shifts caused by heterogeneous deployment condition…
LURE: Latent Space Unblocking for Multi-Concept Reawakening in Diffusion Models
Mengyu Sun, Ziyuan Yang, Andrew Beng Jin Teoh +3
Concept erasure aims to suppress sensitive content in diffusion models, but recent studies show that erased concepts can still be reawakened, revealing vulnerabilities in erasure m…
Federated Learning for Large Models in Medical Imaging: A Comprehensive Review
Mengyu Sun, Ziyuan Yang, Yongqiang Huang +5
Artificial intelligence (AI) has demonstrated considerable potential in the realm of medical imaging. However, the development of high-performance AI models typically necessitates…
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…
Patient-Level Anatomy Meets Scanning-Level Physics: Personalized Federated Low-Dose CT Denoising Empowered by Large Language Model
Ziyuan Yang, Yingyu Chen, Zhiwen Wang +3
Reducing radiation doses benefits patients, however, the resultant low-dose computed tomography (LDCT) images often suffer from clinically unacceptable noise and artifacts. While d…
Plaintext-Free Deep Learning for Privacy-Preserving Medical Image Analysis via Frequency Information Embedding
Mengyu Sun, Ziyuan Yang, Maosong Ran +3
In the fast-evolving field of medical image analysis, Deep Learning (DL)-based methods have achieved tremendous success. However, these methods require plaintext data for training…
A Dual-Level Cancelable Framework for Palmprint Verification and Hack-Proof Data Storage
Ziyuan Yang, Ming Kang, Andrew Beng Jin Teoh +4
In recent years, palmprints have been widely used for individual verification. The rich privacy information in palmprint data necessitates its protection to ensure security and pri…
Energizing Federated Learning via Filter-Aware Attention
Ziyuan Yang, Zerui Shao, Huijie Huangfu +5
Federated learning (FL) is a promising distributed paradigm, eliminating the need for data sharing but facing challenges from data heterogeneity. Personalized parameter generation…
Privacy-Preserving Encrypted Low-Dose CT Denoising
Ziyuan Yang, Huijie Huangfu, Maosong Ran +3
Deep learning (DL) has made significant advancements in tomographic imaging, particularly in low-dose computed tomography (LDCT) denoising. A recent trend involves servers training…
Physics-Driven Spectrum-Consistent Federated Learning for Palmprint Verification
Ziyuan Yang, Andrew Beng Jin Teoh, Bob Zhang +2
Palmprint as biometrics has gained increasing attention recently due to its discriminative ability and robustness. However, existing methods mainly improve palmprint verification w…
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…