AMFL: Resource-Efficient Adaptive Metaverse-Based Federated Learning for the Human-Centric Augmented Reality Applications-Reference-Cited by-同舟云学术

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AMFL: Resource-Efficient Adaptive Metaverse-Based Federated Learning for the Human-Centric Augmented Reality Applications

Published:2024 Issue: Volume: Page:1-15
ISSN:2162-237X
Container-title:IEEE Transactions on Neural Networks and Learning Systems
language:
Short-container-title:IEEE Trans. Neural Netw. Learning Syst.

Author:

Qiao Dewen¹,Qian Liangxin²^ORCID,Guo Songtao¹^ORCID,Zhao Jun²^ORCID,Zhou Pengzhan¹^ORCID

Affiliation:

1. Key Laboratory of Dependable Service Computing in Cyber Physical Society (Ministry of Education) and the College of Computer Science, Chongqing University, Chongqing, China

2. College of Computing and Data Science, Nanyang Technological University, Singapore, Singapore

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/5962385/6104215/10562335.pdf?arnumber=10562335

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