Density Based Traffic Control System with Convolutional Neural Network

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Density Based Traffic Control System with Convolutional Neural Network

Density Based Traffic Control System with Convolutional Neural Network

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Saple Mrunali R. / Jadhav Tejaswini M. / Kode Saurabh Y. / Gargi

We present a real-time traffic flow controller structure that can keep traffic under control using image processing techniques. In this way, a camera is used in every section of the robot to take pictures of the traffic where traffic jams will appear. The number of vehicles in these images is designed using image processing tools. In the proposed image, green and red signals are represented using LEDs and the diminished green signal supervisor is signified by a specific presentation.

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Title :

Density Based Traffic Control System with Convolutional Neural Network

Contributors:

Saple Mrunali R. (author) / Jadhav Tejaswini M. (author) / Kode Saurabh Y. (author) / Gargi (author)

Published in:

ITM Web of Conferences, Vol 44, p 03045 (2022)

Publication date :

2022

ISSN :

DOI :

https://doi.org/10.1051/itmconf/20224403045

Type of media :

Article (Journal)

Type of material :

Electronic Resource

Language :

Unknown

Keywords :

real time , traffic light control , vehicle count , Information technology , T58.5-58.64

Metadata by DOAJ is licensed under CC BY-SA 1.0

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