Traffic Sign Classification for Autonomous Vehicles Using Split and Federated Learning Underlying 5G-Reference-Cited by-同舟云学术

Traffic Sign Classification for Autonomous Vehicles Using Split and Federated Learning Underlying 5G

Published:2023 Issue: Volume:4 Page:877-892
ISSN:2644-1330
Container-title:IEEE Open Journal of Vehicular Technology
language:
Short-container-title:IEEE Open J. Veh. Technol.

Author:

Padaria Ali Asgar¹^ORCID,Mehta Aryan Alpesh¹^ORCID,Jadav Nilesh Kumar¹^ORCID,Tanwar Sudeep¹^ORCID,Garg Deepak²^ORCID,Singh Anupam³^ORCID,Pau Giovanni⁴^ORCID,Sharma Gulshan⁵^ORCID

Affiliation:

1. Department of Computer Science and Engineering, Institute of Technology, Nirma University, Ahmedabad, India

2. School of Computer Science and Artificial Intelligence, SR University, Warangal, India

3. Department of Computer Science and Engineering, Graphic Era Hill University, Dehradun, India

4. Faculty of Engineering and Architecture, Kore University of Enna, Enna, Italy

5. Department of Electrical Engineering Technology, University of Johannesburg, Johannesburg, South Africa

Funder

Kore University of Enna, Italy

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/8782711/9932544/10288388.pdf?arnumber=10288388

Reference24 articles.

1. SAGE: A S plit- A rchitecture Methodolo g y for E fficient End-to-End Autonomous Vehicle Control

2. Very deep convolutional networks for large-scale image recognition;simonyan;Proc 3rd Int Conf Learn Representations,0

3. GeFL: Gradient Encryption-Aided Privacy Preserved Federated Learning for Autonomous Vehicles

4. Semi-supervised Learning in Distributed Split Learning Architecture and IoT Applications

5. The future of industrial-grade edge AI, NVIDIA jetson AGX orin industrial module,2023

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