• Volodymyr Kharchenko National Aviation University
  • Iurii Chyrka National Aviation University



Convolutional neural network, object detection, real-time processing, unmanned aerial vehicle


Purpose: The represented research results are aimed to benchmark performance of state-of-the-art methods of objects detection. There were tested two popular single-stage neural networks based on the “you only looks once” approach. Methods: convolutional neural network, logistic regression, probabilistic theory, stochastic gradient descent. Results: The considered artificial neural network architectures for objects detection has been trained and applied for the particular task of the airplanes detection in aerial images taken from unmanned aerial vehicles and satellites. Discussion: Presented results of experimental verification prove their high detection ability, location precision and real-time processing speed using modern graphics processing unit. The considered neural networks can be easily re-trained for detection of different classes of ground objects.

Author Biographies

Volodymyr Kharchenko, National Aviation University

Doctor of Engineering Sciences. Professor.

Vice-Rector on Scientific Work of the National Aviation University, Kyiv, Ukraine.

Winner of the State Prize of Ukraine in Science and Technology, Honorable Worker of Science and Technology of Ukraine.

Education: Kyiv Institute of Civil Aviation Engineers, Kyiv, Ukraine.

Research area: management of complex socio-technical systems, air navigation systems and automatic decision-making systems aimed at avoidance conflict situations, space information technology design, air navigation services in Ukraine provided by CNS/АТМ systems

Iurii Chyrka, National Aviation University

Candidate of Engineering Sciences. Senior researcher.

National Aviation University.

Education: National Aviation University, Kyiv, Ukraine (2011).

Research area: computer vision, machine learning, control systems, radar signals processing, acoustic holography, and applied statistics.


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How to Cite

Kharchenko, V., & Chyrka, I. (2018). AIRPLANES DETECTION IN AERIAL IMAGES USING YOLO NEURAL NETWORK. Proceedings of National Aviation University, 76(3), 8–15.




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