Energy-Efficient Power Control for Multiple-Task Split Inference in UAVs: A Tiny Learning-Based Approach-Reference-Cited by-同舟云学术

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Energy-Efficient Power Control for Multiple-Task Split Inference in UAVs: A Tiny Learning-Based Approach

Published:2024-06-15 Issue:12 Volume:11 Page:21146-21157
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Zhao Chenxi¹^ORCID,Sheng Min¹^ORCID,Liu Junyu¹^ORCID,Chu Tianshu¹,Li Jiandong¹^ORCID

Affiliation:

1. State Key Laboratory of Integrated Service Networks, Institute of Information Science, Xidian University, Xi’an, Shaanxi, China

Funder

National Key Research and Development Program of China

Natural Science Foundation of China

Key Industry Innovation Chain of Shaanxi

Major Key Project of PCL

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6488907/10551641/10445443.pdf?arnumber=10445443

Reference30 articles.

1. UAV-Based IoT Platform: A Crowd Surveillance Use Case

2. Blockchain-Based Lightweight Authentication for Resilient UAV Communications: Architecture, Scheme, and Future Directions

3. A Survey on the Convergence of Edge Computing and AI for UAVs: Opportunities and Challenges

4. Communication-Computation Trade-off in Resource-Constrained Edge Inference

5. Wireless Distributed Learning: A New Hybrid Split and Federated Learning Approach

Cited by 1 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. Multi-UAV Hierarchical Intelligent Traffic Offloading Network Optimization Based on Deep Federated Learning;IEEE Internet of Things Journal;2024-06-15

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