Assisted Target Detection in Airborne Search and Rescue

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dc.contributor.advisorElder, James H.
dc.contributor.authorTaheri-Shirazi, Maryam
dc.date.accessioned2020-11-13T14:02:50Z
dc.date.available2020-11-13T14:02:50Z
dc.date.copyright2020-10
dc.date.issued2020-11-13
dc.date.updated2020-11-13T14:02:49Z
dc.degree.disciplineElectrical and Computer Engineering
dc.degree.levelMaster's
dc.degree.nameMASc - Master of Applied Science
dc.description.abstractFinding and rescuing people from downed aircraft is challenging in many parts of the world, including Canada. Because the Canadian military still relies on the naked eye to conduct searches, airborne search and rescue could benefit greatly from advanced sensor systems. Partial automation of target detection could alleviate operator workload and potentially improve rescue efforts. One of the obstacles to developing such a system has been the lack of a large, realistic, and ground-truthed search and rescue (SAR) dataset. I used a new dataset for airborne SAR collected in 2014 by the National Research Council Flight Research Laboratory (NRC-FRL) and labeled approximately 40,000 frames, to extract roughly 20,000 negative and 20,000 positive images. Then I tested three ATD methods on this dataset in order to develop more advanced assisted target detection algorithms for thermal infrared (IR) images.
dc.identifier.urihttp://hdl.handle.net/10315/37992
dc.languageen
dc.rightsAuthor owns copyright, except where explicitly noted. Please contact the author directly with licensing requests.
dc.subjectComputer science
dc.subject.keywordsMaryam Taheri-Shirazi
dc.subject.keywordsSearch and Rescue Dataset
dc.subject.keywordsMachine Learning
dc.subject.keywordsDeep Learning
dc.subject.keywordsObject Detection
dc.titleAssisted Target Detection in Airborne Search and Rescue
dc.typeElectronic Thesis or Dissertation

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