Abstract
The objects detector on radar images description is given, which implements the local inhomogeneities detection using the CFAR algorithm with their subsequent two-alternative classification («object» or «background») by a deep convolutional neural networkю. Using the MSTAR dataset, it was shown that in the case of a homogeneous background, the detection results can be considered satisfactory if SNR on image is more than 5 dB, and completely disrupted if SNR less then minus 5 dB.
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