JOURNAL ARTICLE

Deep Learning Based Vehicle Detection From Aerial Images

Abstract

With the help of today's developing technology; many applications such as traffic monitoring, target detection, empty parking lot assignment etc. have become applicable with machine learning and deep learning methods. These applications are aimed to determine the desired object from the photographs. In this study, it is aimed to develop an approach that able to identify the vehicles through aerial images by using the YOLO (You Only Look Once) algorithm, feeding it with a trained convolutional neural network structure. As a result of the study, an application that can detect vehicles was developed, increased the performance rate of the YOLO algorithm by 3.2%.

Keywords:
Object detection Deep learning Computer science Convolutional neural network Artificial intelligence Computer vision Artificial neural network Machine learning Pattern recognition (psychology)

Metrics

17
Cited By
1.36
FWCI (Field Weighted Citation Impact)
23
Refs
0.83
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Neural Network Applications
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Vehicle License Plate Recognition
Physical Sciences →  Engineering →  Media Technology
Video Surveillance and Tracking Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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