Araç İçi Sesinden Aracı Tanıma ve Sınıflandırma
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Date
2021
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Konya Technical University
Open Access Color
GOLD
Green Open Access
No
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Publicly Funded
No
Abstract
Günümüzde, teknolojik imkanların hızla gelişmesiyle ses sınıflandırma uygulamalarının sayıları da artmakta ve popüler bir çalışma alanı haline gelmektedir. Bu çalışmada, amacımız durağan halde bir aracın üretmiş olduğu sesi kullanarak "aracın sesli imzasını" üretmek ve aracın sınıflandırılması için kullanmaktır. Çalışan bir aracın sesi; motor sesi, titreşimden kaynaklı sesler, rüzgâr sesleri gibi bazı seslerin bir araya gelmesiyle oluşur. Uygulamada 22 aracın rölantideki sesleri kaydedilmiş ve Local Binary Pattern (LBP) ve Cubic SVM algoritmaları kullanılarak %95,2 oranında başarılı sınıflandırılmıştır. Ayrıca, elde edilen sonuçlar literatürdeki çalışmalarla karşılaştırılmıştır.
Today, with the rapid development of technological possibilities, the number of sound classification applications are increasing and becoming a popular field for researchers. In this study, our aim is to extract "vehicle sound signature" by using the sound produced by the vehicle at idle mode. After that to use this sound signature for the classification of the vehicle. The sound of a working vehicle at idle mode consist of some noises cause by engine, vibration, wind etc. In practice, the sounds of 22 vehicles at idle mode were recorded and 95.2% successful classification was made by using the Local Binary Pattern (LBP) method and the Cubic SVM algorithm. In addition, the results were analyzed by comparing them with similar studies in the related literature.
Today, with the rapid development of technological possibilities, the number of sound classification applications are increasing and becoming a popular field for researchers. In this study, our aim is to extract "vehicle sound signature" by using the sound produced by the vehicle at idle mode. After that to use this sound signature for the classification of the vehicle. The sound of a working vehicle at idle mode consist of some noises cause by engine, vibration, wind etc. In practice, the sounds of 22 vehicles at idle mode were recorded and 95.2% successful classification was made by using the Local Binary Pattern (LBP) method and the Cubic SVM algorithm. In addition, the results were analyzed by comparing them with similar studies in the related literature.
Description
DergiPark: 755710
konjes
konjes
Keywords
ses sınıflandırma, araç tanıma, sesli imza, araç sınıflandırma, sound classification, vehicle recognition, voice signature, vehicle classification, ses sınıflandırma;araç tanıma;sesli imza;araç sınıflandırma, sound classification;vehicle recognition;voice signature;vehicle classification, Engineering, Mühendislik
Turkish CoHE Thesis Center URL
Fields of Science
0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology
Citation
WoS Q
Q4
Scopus Q
N/A

OpenCitations Citation Count
N/A
Source
Konya Mühendislik Bilimleri Dergisi
Volume
9
Issue
1
Start Page
129
End Page
136
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