Privacy Preserving Palmprint Recognition via Federated Metric Learning-Reference-Cited by-同舟云学术

Privacy Preserving Palmprint Recognition via Federated Metric Learning

Author:

Shao Huikai¹^ORCID,Liu Chengcheng²^ORCID,Li Xiaojiang²^ORCID,Zhong Dexing³^ORCID

Affiliation:

1. School of Automation Science and Engineering and School of Mathematics and Statistics, Xi’an Jiaotong University, Shaanxi, Xi’an, China

2. Xi’an Yizhanghui Technology Company, Shaanxi, Xi’an, China

3. School of Automation Science and Engineering, Xi’an Jiaotong University, Shaanxi, Xi’an, China

Funder

National Natural Science Foundation of China

Zhejiang Provincial Natural Science Foundation of China

Young Talent Fund of Association for Science and Technology, Shaanxi, China

Xi’an Science and Technology Project

Beilin District Science and Technology Project

Shaanxi Post-Doctoral Research Project Funding

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Safety, Risk, Reliability and Quality

Link

Reference71 articles.

1. FedMD: Heterogenous federated learning via model distillation;li;Proc Workshop Federated Learn Data Privacy Confidentiality (NeurIPS),2019

5. Agnostic federated learning;mohri;Proc 36th Int Conf Mach Learn (ICML),2019

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

2. Dynamic Secure Multi Broad Network for Privacy Preserving of Streaming Data;IEEE Transactions on Emerging Topics in Computational Intelligence;2024-08