Unmanned aerial vehicles (UAVs) play important role in human life. Today there is
a high rate of technology development in the field of unmanned aerial vehicles production.
Along with the growing popularity of the private UAVs, the threat of using drones
for terrorist attacks and other illegal purposes is also significantly increasing.
In this case the UAVs detection and tracking in city conditions are very important.
In this paper we consider the possibility of detecting drones from a video image.
The work compares the effectiveness of fast neural networks YOLO v.3, YOLO v.3-SPP
and YOLO v.4. The experimental tests showed the effectiveness of using the YOLO v.4
neural network for real-time UAVs detection without significant quality losses. To
estimate the detection range, a calculation of the projection target points in different
ranges was performed. The experimental tests showed possibility to detect UAVs size
of 0.3 m at a distance about 1 km with Precision more than 90 %.
