Underwater acoustic target recognition using graph convolutional neural networks

Abstract

Motivated by recent progress in signal processing on graphs and convolutional neural networks, we have developed an underwater acoustic target recognition system based on graph convolutional neural networks. We evaluate our framework by application to various real-world datasets and validate its effectiveness. Our experiments demonstrate that the proposed approach achieves high classification accuracy.