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dc.contributor.advisorScrofani, James
dc.contributor.advisorTummala, Murali
dc.contributor.authorSchaus, Brian M.
dc.dateMarch 2015
dc.date.accessioned2015-05-06T19:17:57Z
dc.date.available2015-05-06T19:17:57Z
dc.date.issued2015-03
dc.identifier.urihttp://hdl.handle.net/10945/45252
dc.descriptionApproved for public release; distribution is unlimiteden_US
dc.description.abstractTechniques for classifying maritime domain targets-of-interest within images are explored in this thesis. Geometric and photometric features within each image are extracted from processed images and are used to train a neural network. The trained neural network is tested with features of a known object. In the binary classification case, the neural network is used to determine whether a ship is present or not present in the image. In the multi-class and multi-level classification cases, the neural network is used to determine if the object belongs to one of four classes specified: warship, cargo ship, small boat, or other. The Hough transformation is used to identify and characterize linear patterns exhibited by objects in images. As an alternative to geometric and photometric features to classify targets-of-interest, these linear patterns are used to train a neural network. The performance of the neural network is then tested for binary, multi-class, and multi-level classification schemes. The development of neural-network-based techniques for automated target-of-interest classification is a significant result of this thesis.en_US
dc.publisherMonterey, California: Naval Postgraduate Schoolen_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.en_US
dc.titleImproving maritime domain awareness using neural networks for target of interest classificationen_US
dc.typeThesisen_US
dc.contributor.departmentElectrical and Computer Engineering
dc.contributor.departmentElectrical and Computer Engineeringen_US
dc.subject.authorNeural networksen_US
dc.subject.authorfeature extractionen_US
dc.subject.authorHough transformationen_US
dc.subject.authorobject detectionen_US
dc.subject.authorobject classificationen_US
dc.subject.authormaritime domain awarenessen_US
dc.description.serviceLieutenant, United States Navyen_US
etd.thesisdegree.nameMaster of Science in Electrical Engineeringen_US
etd.thesisdegree.levelMastersen_US
etd.thesisdegree.disciplineElectrical Engineeringen_US
etd.thesisdegree.grantorNaval Postgraduate Schoolen_US


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