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Federated Transfer Learning for IIoT Devices With Low Computing Power Based on Blockchain and Edge Computing

  • Published:2021 Issue: Volume:9 Page:98630-98638
  • ISSN:2169-3536
  • Container-title:IEEE Access
  • language:
  • Short-container-title:IEEE Access

Author:

Zhang PeiyingORCID,Sun HaoORCID,Situ JingyiORCID,Jiang ChunxiaoORCID,Xie DongliangORCID

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Shandong Provincial Natural Science Foundation

Major Scientific and Technological Projects of China National Petroleum Corporation

Open Foundation of State Key Laboratory of Networking and Switching Technology

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Cited by 34 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

1. A comprehensive review on Federated Learning for Data-Sensitive Application: Open issues & challenges;Engineering Applications of Artificial Intelligence;2024-07

2. An optimized federated learning method based on soft label grouping for heterogeneous IoT;Cluster Computing;2024-04-13

3. Special Issue on Transportation Big Data and Its Applications;Applied Sciences;2024-02-13

4. Combining Machine Learning and Edge Computing: Opportunities, Challenges, Platforms, Frameworks, and Use Cases;Electronics;2024-02-03

5. Blockchain-Aided Privacy Preserving Framework for Federated Learning;2024 International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics (IITCEE);2024-01-24
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