DEEP-FEL: Decentralized, Efficient and Privacy-Enhanced Federated Edge Learning for Healthcare Cyber Physical Systems-Reference-Cited by-同舟云学术

DEEP-FEL: Decentralized, Efficient and Privacy-Enhanced Federated Edge Learning for Healthcare Cyber Physical Systems

Author:

Lian Zhuotao¹^ORCID,Yang Qinglin²^ORCID,Wang Weizheng³^ORCID,Zeng Qingkui⁴^ORCID,Alazab Mamoun⁵^ORCID,Zhao Hong¹^ORCID,Su Chunhua¹^ORCID

Affiliation:

1. Department of Computer Science and Engineering, The University of Aizu, Aizuwakamatsu, Japan

2. School of Intelligent System Engineering, Sun Yat-sen University, Guangzhou, Guangdong Province, China

3. Department of Computer Science, City University of Hong Kong, Hong Kong, Hong Kong

4. School of Electronics and Information Engineering, Nanjing University of Information Science & Technology, Nanjing, China

5. Department of IT, Melbourne Polytechnic, Prahran Campus, Melbourne, VIC, Australia

Funder

Ministry of Education

National Research Foundation of Korea

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Control and Systems Engineering

Link

Reference50 articles.

2. Collaborative federated learning for healthcare: Multi-modal COVID-19 diagnosis at the edge;qayyum,2021

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