Solutions to increase the probability of the accuracy of UAV recognition target based on artificial intelligence
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https://doi.org/10.54939/1859-1043.j.mst.FEE.2023.105-110Keywords:
UAV; Residual; Loss function; Radar target recognition; Deep learning.Abstract
In this article, we propose to build a neural network model with a combined Residual-Inception structure (named RINet) and use the weighted Focal Loss loss during training to perform radar target classification based on the RAD-DAR dataset. The RINet model incorporating the proposed loss function has an average target classification accuracy of 98.72%, in which the probability of correctly identifying the UAV is up to 99.81%.
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