Lightweight and Efficient Convolutional Neural Network for Traffic Signs Classification-Reference-Cited by-同舟云学术

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Lightweight and Efficient Convolutional Neural Network for Traffic Signs Classification

Published:2022-05-28 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)
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Author:

Kherraki Amine¹,Maqbool Muaz²,Ouazzani Rajae El¹

Affiliation:

1. School of Technology Moulay Ismail University of Meknes,IMAGE Laboratory,Meknes,Morocco

2. OMNO AI,AI Department,Lahore,Pakistan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9875397/9875429/09875868.pdf?arnumber=9875868

Reference31 articles.

1. Traffic Sign Detection and Recognition Based on Convolutional Neural Network

2. Novel deep learning model for traffic sign detection using capsule networks;kumar,2018

3. Multi-column deep neural networks for image classification

4. Traffic sign classification using K-d trees and Random Forests

5. Deep neural network for traffic sign recognition systems: An analysis of spatial transformers and stochastic optimisation methods

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. A Survey on Traffic Sign Classification using Artificial Intelligence Techniques;2024 International Conference on Intelligent Systems and Computer Vision (ISCV);2024-05-08

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