Toward Effective Traffic Sign Detection via Two-Stage Fusion Neural Networks-Reference-Cited by-同舟云学术

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Toward Effective Traffic Sign Detection via Two-Stage Fusion Neural Networks

Published:2024-08 Issue:8 Volume:25 Page:8283-8294
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Li Zhishan¹^ORCID,Chen Hongxu²,Biggio Battista³^ORCID,He Yifan¹^ORCID,Cai Haoran⁴,Roli Fabio³^ORCID,Xie Lei²^ORCID

Affiliation:

1. Institute of Intelligence Science and Engineering, Shenzhen Polytechnic University, Shenzhen, China

2. State Key Laboratory of Industrial Control Technology and the Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou, China

3. Department of Electrical and Electronic Engineering, University of Cagliari, Cagliari, Italy

4. Huawei Technology Company Ltd., Nanjing, China

Funder

Jianbing Lingyan Foundation of Zhejiang Province, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6979/10621861/10474579.pdf?arnumber=10474579

Reference52 articles.

1. SSD: Single Shot MultiBox Detector

2. YOLOv3: An incremental improvement;Redmon;arXiv:1804.02767,2018

3. EfficientDet: Scalable and Efficient Object Detection

4. The Pascal Visual Object Classes Challenge: A Retrospective

5. Microsoft COCO: Common Objects in Context

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. YOLO-ADual: A Lightweight Traffic Sign Detection Model for a Mobile Driving System;World Electric Vehicle Journal;2024-07-21

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