Toward Efficient and Secure Object Detection With Sparse Federated Training Over Internet of Vehicles-Reference-Cited by-同舟云学术

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Toward Efficient and Secure Object Detection With Sparse Federated Training Over Internet of Vehicles

Published:2024 Issue: Volume: Page:1-14
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Qian Yuwen¹^ORCID,Rao Luping¹,Ma Chuan²^ORCID,Wei Kang³^ORCID,Ding Ming⁴^ORCID,Shi Long¹

Affiliation:

1. School of Electronic Engineering and Optoelectronic Technology, Nanjing University of Science and Technology, Nanjing, Jiangsu, China

2. School of Computer Science, Chongqing University, Chongqing, China

3. Department of Computing, The Hong Kong Polytechnic University, Hong Kong, China

4. Data61, CSIRO, Sydney, NSW, Australia

Funder

Jiangsu Specially-Appointed Professor Program 2021

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6979/4358928/10510160.pdf?arnumber=10510160

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1. Communication-Efficient and Private Federated Learning with Adaptive Sparsity-Based Pruning on Edge Computing;Electronics;2024-08-29

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