Abstract
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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
