An Intelligent Traffic Signal Detection System Using Deep Learning

International Journal of VLSI & Signal Processing

© 2021 by SSRG - IJVSP Journal

Volume 8 Issue 1

Year of Publication : 2021

Authors : Ms.S.Supraja, Dr.P.Ranjith Kumar

10.14445/23942584/IJVSP-V8I1P102

How to Cite?

Ms.S.Supraja, Dr.P.Ranjith Kumar, "An Intelligent Traffic Signal Detection System Using Deep Learning," SSRG International Journal of VLSI & Signal Processing, vol. 8,  no. 1, pp. 5-9, 2021. Crossref, https://doi.org/10.14445/23942584/IJVSP-V8I1P102

Abstract:

The proposed framework gives a precise method for traffic signals with insignificant human exertion. In the PC vision local area, the acknowledgment and recognition of traffic signs are well-informed issues. In this work, the issue of identifying and perceiving countless traffic-signs classifications is addressed for programmed traffic signals by utilizing Squeeze Net CNN. This framework has a few upgrades that are assessed on the discovery of traffic signs utilizing deep learning. This brings about an improved general execution with an insignificant error rate, and the outcomes are accounted for on exceptionally testing traffic-sign classifications that have not yet been processed in past works.

Keywords:

Squeeze Net CNN, Traffic sign inventory, Detecting, Recognizing, Deep learning.

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