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                  <text>VOL. 19, NO. 3 2021</text>
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                <text>TELKOMNIKA Telecommunication, Computing, Electronics and Control&#13;
A comprehensive review of vehicle detection using computer vision</text>
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                <text>Computer vision&#13;
GMM&#13;
Intelligent transport system&#13;
KDE&#13;
Vehicle detection</text>
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                <text>A crucial step in designing intelligent transport systems (ITS) is vehicle detection.&#13;
The challenges of vehicle detection in urban roads arise because of camera position,&#13;
background variations, occlusion, multiple foreground objects as well as vehicle pose.&#13;
The current study provides a synopsis of state-of-the-art vehicle detection techniques,&#13;
which are categorized according to motion and appearance-based techniques starting&#13;
with frame differencing and background subtraction until feature extraction, a more&#13;
&#13;
complicated model in comparison. The advantages and disadvantages among the tech-&#13;
niques are also highlighted with a conclusion as to the most accurate one for vehicle&#13;
&#13;
detection.</text>
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                <text>Aymen Fadhil Abbas, Usman Ullah Sheikh, Fahad Taha AL-Dhief, Mohd Norzali Haji Mohd</text>
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                <text>http://journal.uad.ac.id/index.php/TELKOMNIKA</text>
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                <text>Dec 3, 2020</text>
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                <text>peri irawan</text>
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        <name>Computer Vision</name>
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        <name>GMM</name>
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        <name>Intelligent transport system</name>
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        <name>Jurnal Nasional Informatika</name>
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        <name>Vehicle detection</name>
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