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dc.contributor.advisorMarcellin, Michael W.en
dc.contributor.authorHung, David
dc.contributor.authorMcKeever, Kennon
dc.contributor.authorRamirez, Ricardo
dc.date.accessioned2018-03-02T23:43:56Z
dc.date.available2018-03-02T23:43:56Z
dc.date.issued2017-10
dc.identifier.issn0884-5123
dc.identifier.issn0074-9079
dc.identifier.urihttp://hdl.handle.net/10150/626985
dc.description.abstractAccurate image classification is one of the core challenges in computer vision. At the annual AUVSI SUAS competition, this challenge is faced in the form of ground target classification from an unmanned aerial vehicle (UAV). Additionally, due to the constraints imposed by the UAV platform, the system design must consider factors such as size, weight, and power consumption. To meet performance requirements while respecting such limitations, the system was broken into two subsystems: an onboard subsystem and a ground based subsystem. This design allows the onboard subsystem, comprised of a DSLR camera and single-board computer, to capture ground target images and perform rudimentary target detection and localization. For further processing and to ultimately classify the targets in each image, data packets are sent to the ground-based subsystem via a 5 GHz wireless link. Convolutional networks are utilized on the ground to achieve state-of-the-art accuracy in classification.
dc.description.sponsorshipInternational Foundation for Telemeteringen
dc.language.isoen_USen
dc.publisherInternational Foundation for Telemeteringen
dc.relation.urlhttp://www.telemetry.org/en
dc.rightsCopyright © held by the author; distribution rights International Foundation for Telemeteringen
dc.titleHYBRID AUTOMATED UAV TARGET RECOGNITION SYSTEMen_US
dc.typetexten
dc.typeProceedingsen
dc.contributor.departmentUniv Arizona, Dept Elect & Comp Engnen
dc.identifier.journalInternational Telemetering Conference Proceedingsen
dc.description.collectioninformationProceedings from the International Telemetering Conference are made available by the International Foundation for Telemetering and the University of Arizona Libraries. Visit http://www.telemetry.org/index.php/contact-us if you have questions about items in this collection.
refterms.dateFOA2018-06-15T02:49:04Z
html.description.abstractAccurate image classification is one of the core challenges in computer vision. At the annual AUVSI SUAS competition, this challenge is faced in the form of ground target classification from an unmanned aerial vehicle (UAV). Additionally, due to the constraints imposed by the UAV platform, the system design must consider factors such as size, weight, and power consumption. To meet performance requirements while respecting such limitations, the system was broken into two subsystems: an onboard subsystem and a ground based subsystem. This design allows the onboard subsystem, comprised of a DSLR camera and single-board computer, to capture ground target images and perform rudimentary target detection and localization. For further processing and to ultimately classify the targets in each image, data packets are sent to the ground-based subsystem via a 5 GHz wireless link. Convolutional networks are utilized on the ground to achieve state-of-the-art accuracy in classification.


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