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. 
Peter J. Dugan, Christopher W. Clark, Yann Andr\'e LeCun, Sofie M. Van   Parijs
cs.DC