Emergency Vehicle Detection Using Deep ConvNet2D and Computer Vision-Reference-Cited by-同舟云学术

Emergency Vehicle Detection Using Deep ConvNet2D and Computer Vision

Published:2024-02-22 Issue: Volume:2 Page:1-4
ISSN:
Container-title:2024 Second International Conference on Emerging Trends in Information Technology and Engineering (ICETITE)
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Author:

Poongavanam Elumalaivasan¹,A Prathik.²,T Munirathinam.³,V Kayalvizhi.⁴,R Rajesh.⁵,C Mahavishnu.⁶

Affiliation:

1. SRM Institute of Science and Technology, Kattankulathur,Department of Data Science and Business Systems,Chennai,India

2. Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology,Department of Computer Science and Engineering,Chennai,India

3. Sona College of Technology,Department of Information Technology,Salem,India

4. School of Computer Science and Engineering and Information Science, Presidency University,Bangalore,India

5. School of Computer Science and Engineering, Vellore Institute of Technology,Chennai,India

6. Shreenivasa Engineering College,Department of Computer Science and Engineering,Dharmapuri,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10493200/10493145/10493508.pdf?arnumber=10493508

Reference15 articles.

1. A Novel Framework for Vehicle Detection and Classification Using Enhanced YOLO-v7 and GBM to Prioritize Emergency Vehicle;Vikruthi;International Journal of Intelligent Systems and Applications in Engineering,2024

2. Acoustic Based Emergency Vehicle Detection Using Ensemble of deep Learning Models

3. Emergency Vehicle Detection in Heavy Traffic using Deep ConvNet2D and ComputerVision;Sanjay,2022

4. Artificial intelligence for smart cities: locational planning and dynamic routing of emergency vehicles;Ugur,2022

5. Traffic Lane Localization using Clothoid Road Model