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A Novel Approach for Vehicle Type Classification and Speed Prediction using Deep Learning

Publication Type : Journal Article

Source : Journal of Computational and Theoretical Nanoscience, Volume 17, Number 5, pp. 2237-2242, [SCOPUS], 2020. DOI: https://doi.org/10.1166/jctn.2020.88770

Url : https://www.ingentaconnect.com/content/asp/jctn/2020/00000017/00000005/art00039;jsessionid=chfef3j9e09r3.x-ic-live-01

Campus : Chennai

School : School of Computing

Year : 2020

Abstract : In Vehicles automation system, Classification and speed detection has become an important research challenge in road safety and intelligent transportation system. Many systems like pattern recognition, image processing and machine learning technologies have overcome numerous hindrances to accomplish this goal. In this paper, we demonstrate a speed detection system and vehicle type classification founded on deep learning technique. Moreover, we built up Modular Neural Network (MNN) architecture, advancement algorithm and its parameters are acquired by training dataset. This integrated part of a system will enhance to finding in automation detection and traffic flow management system.

Cite this Research Publication : E. S. Madhan, R. Annamalai, S. Neelakandan, "A Novel Approach for Vehicle Type Classification and Speed Prediction using Deep Learning," Journal of Computational and Theoretical Nanoscience, Volume 17, Number 5, pp. 2237-2242, [SCOPUS], 2020. DOI: https://doi.org/10.1166/jctn.2020.88770

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