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Deep convolutional neural network target classification for underwater synthetic aperture sonar imagery

August 12, 2019

Abstract: In underwater synthetic aperture sonar (SAS) imagery, there is a need for accurate target recognition algorithms. Automated detection of underwater objects has many applications, not the least of which being the safe extraction of dangerous explosives. In this paper, we discuss experiments on a deep learning approach to binary classification of target and non-target […]

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A Target Classification Algorithm for Underwater Synthetic Aperture Sonar Imagery

May 3, 2018

Abstract: The ability to discern the characteristics of the seafloor has many applications. Due to minimal visibility, Synthetic Aperture Sonar Imagery (SAS) uses sonar to produce a texture map of the seabed below. In this paper, we discuss an approach to detecting targets from varying seafloor contexts. The approach begins with one or more anomaly […]

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