Military objects detection using a convolutional neural network on radar images formed in jamming conditions
Year: 2025
Type: article
Abstract: The MSTAR objects detection on noised radar images using the YOLOv4-tiny detector results are presented. It has been shown that on a homogeneous background detector work is satisfactory when the signal-to-noise ratio is 10 dB or more, and completely disrupted when the signal-to-noise ratio is less than 0 dB.
Source: Journal of Radio Electronics
Author: I.F. Kupryashkin
Language: English
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4407616658