no code implementations • 19 Nov 2023 • Chengrui Gao, Ziyuan Yang, Min Zhu, Andrew Beng Jin Teoh
This paper proposes a scale-aware competitive network (SAC-Net), which includes the Inner-Scale Competition Module (ISCM) and the Across-Scale Competition Module (ASCM) to capture texture characteristics related to orientation and scale.
no code implementations • 18 Nov 2023 • Ziyuan Yang, Zerui Shao, Huijie Huangfu, Hui Yu, Andrew Beng Jin Teoh, Xiaoxiao Li, Hongming Shan, Yi Zhang
Federated learning (FL) is a promising distributed paradigm, eliminating the need for data sharing but facing challenges from data heterogeneity.
1 code implementation • 9 Nov 2023 • Meiling Fang, Marco Huber, Julian Fierrez, Raghavendra Ramachandra, Naser Damer, Alhasan Alkhaddour, Maksim Kasantcev, Vasiliy Pryadchenko, Ziyuan Yang, Huijie Huangfu, Yingyu Chen, Yi Zhang, Yuchen Pan, Junjun Jiang, Xianming Liu, Xianyun Sun, Caiyong Wang, Xingyu Liu, Zhaohua Chang, Guangzhe Zhao, Juan Tapia, Lazaro Gonzalez-Soler, Carlos Aravena, Daniel Schulz
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 International Joint Conference on Biometrics (IJCB 2023).
no code implementations • 13 Oct 2023 • Ziyuan Yang, Huijie Huangfu, Maosong Ran, Zhiwen Wang, Hui Yu, Yi Zhang
In this way, the proposed methods can achieve two merits, the data privacy is well protected and the server model is free from the risk of model leakage.
1 code implementation • IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY 2023 • Ziyuan Yang, Huijie Huangfu, Lu Leng, Bob Zhang, Andrew Beng Jin Teoh, Yi Zhang
The traditional competition mechanism focuses solely on selecting the winner of different channels without considering the spatial information of the features.
1 code implementation • 1 Aug 2023 • Ziyuan Yang, Andrew Beng Jin Teoh, Bob Zhang, Lu Leng, Yi Zhang
Subsequently, we introduce anchor models for short- and long-spectrum, which constrain the optimization directions of local models associated with long- and short-spectrum images.
no code implementations • 18 Jul 2023 • Yingyu Chen, Ziyuan Yang, Chenyu Shen, Zhiwen Wang, Yang Qin, Yi Zhang
Recently, uncertainty-aware methods have attracted increasing attention in semi-supervised medical image segmentation.
2 code implementations • 27 Feb 2023 • Haoyi Niu, Kun Ren, Yizhou Xu, Ziyuan Yang, Yichen Lin, Yi Zhang, Jianming Hu
Autonomous driving and its widespread adoption have long held tremendous promise.
1 code implementation • 13 Dec 2022 • Ziyuan Yang, Yingyu Chen, Huijie Huangfu, Maosong Ran, Hui Wang, Xiaoxiao Li, Yi Zhang
To achieve this goal, in this paper, we propose Robust Split Federated Learning (RoS-FL) for U-shaped medical image networks, which is a novel hybrid learning paradigm of FL and SL.
1 code implementation • 8 Jun 2022 • Ziyuan Yang, Wenjun Xia, Zexin Lu, Yingyu Chen, Xiaoxiao Li, Yi Zhang
The basic assumption of HyperFed is that the optimization problem for each institution can be divided into two parts: the local data adaption problem and the global CT imaging problem, which are implemented by an institution-specific hypernetwork and a global-sharing imaging network, respectively.