Classification of dispersive gunshot calls using a convolutional neural network

Le résumé fourni par la source

A convolutional neural network (CNN) was trained to identify multi-modal gunshots (impulse calls) within large acoustic datasets in shallow-water environments. South Atlantic right whale gunshots were used to train the CNN, and North Pacific right whale (NPRW) gunshots, to which the network was naive, were used for testing. The classifier generalizes to new gunshots from the NPRW and is shown to identify calls which can be used to invert for source range and/or environmental parameters. This can save human analysts hours of manually screening large passive acoustic monitoring datasets.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.