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

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.

preprint2016arXivOpen access
Peter J. DuganChristopher W. ClarkYann André LeCunSofie M. Van Parijs
Distributed, Parallel, and Cluster Computing
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Open access4 authors1 topic
Imported metadata coverageMissing code, dataset, citation and institution fields are tracked without dominating the paper.Details
Citations: 0Reviews: 0Saves: 0Code: not linkedDataset: not linkedInstitutions: 0

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Peter J. DuganChristopher W. ClarkYann André LeCunSofie M. Van Parijs

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