Data Cleansing For Training Vehicle Detection Models

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dc.contributor.author Wang, Guanyu
dc.date.accessioned 2020-05-01T04:49:08Z
dc.date.available 2020-05-01T04:49:08Z
dc.date.copyright 2020 en_US
dc.date.issued 2020-04-30
dc.identifier.uri http://hdl.handle.net/1828/11708
dc.description.abstract In recent years, machine learning has become more and more popular. As a special type of machine learning, supervised learning uses various algorithms to learn from training data and makes predictions about future outcome. In this project, we present our study on data cleansing and its impact on vehicle detection. In the first half, we demonstrate how to collect a clean dataset for training. We also build a website which helps users to annotate and check results online. In the second half, we conduct experiments to find what factors may influence the results and how to get better test results. en_US
dc.language.iso en en_US
dc.rights Available to the World Wide Web en_US
dc.title Data Cleansing For Training Vehicle Detection Models en_US
dc.type project en_US
dc.contributor.supervisor Wu, Kui
dc.degree.department Department of Computer Science en_US
dc.degree.level Master of Science M.Sc. en_US
dc.description.scholarlevel Graduate en_US

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