Vehicle Brand Detection Using Deep Learning Algorithms

Mehmet Furkan KUNDURACI; Humar KAHRAMANLI ÖRNEK

doi:10.18100/ijamec.578497

Research ArticlesverifiedPeer-ReviewedOpen Access

Pages: 70-74

Vehicle Brand Detection Using Deep Learning Algorithms

Mehmet Furkan KUNDURACI fingerprint•

Humar KAHRAMANLI ÖRNEK fingerprint

Publication DateSeptember 30, 2019

Volume / IssueVol. 7, No. 3 (pp. 70-74)

DOI Identifier10.18100/ijamec.578497

subject

Abstract

Today, information technologies are used in almost every stage of life. It seeks to find solutions too many issues and problems. Image processing applications have been widely used in many areas in recent years and are trying to solve problems. Many applications which perform tasks such as classification, counting, measurement, target tracking have been developed. The aim of this study is to provide a solution for different applications using an effective and cost-effective method to detect the brand and model of vehicles. A classification method is implemented using deep neural network in the determination of the vehicle brand. The proposed solution is tested on various images taken from different angles and obtained from different sources. Faster-RCNN method which is one of deep neural networks is used to brand detection of vehicles in this study. It is observed that Faster-RCNN method performs 67.66% classification accuracy.

Keywords:Vehicle brand detectionImage ProcessingDeep Neural NetworksTensorflowFaster-RCNN

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Vehicle Brand Detection Using Deep Learning Algorithms

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