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We aim to investigate advancing the state of the art of detection,classification and localization (DCL) in the field of bioacoustics. The twoprimary goals are to develop transferable technologies for detection andclassification in: (1) the area of advanced algorithms, such as deep learningand other methods; and (2) advanced systems, capable of real-time and archivaland processing. This project will focus on long-term, continuous datasets toprovide automatic recognition, minimizing human time to annotate the signals.Effort will begin by focusing on several years of multi-channel acoustic datacollected in the Stellwagen Bank National Marine Sanctuary (SBNMS) between 2006and 2010. Our efforts will incorporate existing technologies in thebioacoustics signal processing community, advanced high performance computing(HPC) systems, and new approaches aimed at automatically detecting-classifyingand measuring features for species-specific marine mammal sounds within passiveacoustic data.

Phase 1: DCL System Research Using Advanced Approaches for Land-based or  Ship-based Real-Time Recognition and Localization of Marine Mammals - HPC  System Implementation