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dc.contributor.authorBorck, Michael Geoffery
dc.contributor.supervisorProf. Geoff Westen_US
dc.date.accessioned2017-11-13T08:33:58Z
dc.date.available2017-11-13T08:33:58Z
dc.date.issued2016
dc.identifier.urihttp://hdl.handle.net/20.500.11937/57505
dc.description.abstract

This thesis investigates many different feature extraction methods and machine learning algorithms for their usefulness in detecting objects from vehicle-based mobile mapping systems datasets. A comprehensive analysis using performances measures and graphical techniques are applied to identify the best combination of features and classifiers. A system was built enable users who are not programmers to manage image data and to customise their analyses by combining common data analysis tools to fit their needs.

en_US
dc.publisherCurtin Universityen_US
dc.titleFeature Extraction from Multi-modal Mobile Mapping Dataen_US
dc.typeThesisen_US
dcterms.educationLevelPh.D.en_US
curtin.departmentSpatial Scienceen_US
curtin.accessStatusOpen accessen_US
curtin.facultyScience and Engineeringen_US


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