Traffic Sign Recognition using Optimized Federated Learning in Internet of Vehicles-Reference-Cited by-同舟云学术

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Traffic Sign Recognition using Optimized Federated Learning in Internet of Vehicles

Published:2023 Issue: Volume: Page:1-1
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Lian Zhuotao¹^ORCID,Zeng Qingkui²^ORCID,Wang Weizheng³^ORCID,Xu Dequan⁴^ORCID,Meng Weizhi⁵^ORCID,Su Chunhua¹^ORCID

Affiliation:

1. Department of Computer Science and Engineering, University of Aizu, Aizuwakamatsu, Japan

2. School of Electronics and Information Engineering, Nanjing University of Information Science and Technology, Nanjing, China

3. Department of Computer Science, City University of Hong Kong, Hong Kong SAR, China

4. College of Computer Science and Technology, State Key Laboratory of Public Big Data, Guizhou University, Guiyang, China

5. Department of Applied Mathematics and Computer Science, Technical University of Denmark (DTU), Denmark

Funder

Japan Society for the Promotion of Science

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/6488907/6702522/10242044.pdf?arnumber=10242044

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2. Research and Application of the Median Filtering Method in Enhancing the Imperceptibility of Perturbations in Adversarial Examples;Electronics;2024-06-23

3. Passive Safety Assessment of Railroad Trains in Moose Herd Collision Scenarios;Sustainability;2024-01-25

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