Deep learning for acoustic detection of submarines

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This project is devoted to the development of a pattern recognition system for underwater acoustic signals used**in submarine detection. 2-D images will be built from the acoustic signals and their features, and image**classification algorithms will be applied to those images. In particular, the use of deep convolutional networks**will be thoroughly investigated, including strategies to reduce their size and complexity. In order to reduce the**computational and memory requirements, the network will be iteratively reduced in size by removing**redundant connections or connections of lower weight. We will also investigate the possibility of reducing the**number of layers. The use of a cascade of classifiers is also envisioned for improving the efficient of the**detector. A system (i.e., executable software code) that uses pattern recognition to identify signatures from**acoustic spectra will be delivered to the partner.