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arXiv · 1605.00983

Phase 3: DCL System Using Deep Learning Approaches for Land-based or Ship-based Real-Time Recognition and Localization of Marine Mammals - Bioacoustic Applicaitons

Peter J. Dugan·Christopher W. Clark·Yann André LeCun·Sofie M. Van Parijs
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Abstract

Goals of this research phase is to investigate advanced detection and classification pardims useful for data-mining passive large passive acoustic archives. Technical objectives are to develop and refine a High Performance Computing, Acoustic Data Accelerator (HPC-ADA) along with MATLAB based software based on time series acoustic signal Detection cLassification using Machine learning Algorithms, called DeLMA. Data scientists and biologists integrate to use the HPC-ADA and DeLMA technologies to explore data using newly developed techniques aimed at inspection of data extracted at large spatial and temporal scales.

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Peter J. Dugan, Christopher W. Clark, Yann André LeCun, Sofie M. Van Parijs. 2016-05-03. Phase 3: DCL System Using Deep Learning Approaches for Land-based or Ship-based Real-Time Recognition and Localization of Marine Mammals - Bioacoustic Applicaitons. https://arxiv.org/abs/1605.00983

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