Data Cleansing For Training Vehicle Detection Models

dc.contributor.authorWang, Guanyu
dc.contributor.supervisorWu, Kui
dc.date.accessioned2020-05-01T04:49:08Z
dc.date.available2020-05-01T04:49:08Z
dc.date.copyright2020en_US
dc.date.issued2020-04-30
dc.degree.departmentDepartment of Computer Scienceen_US
dc.degree.levelMaster of Science M.Sc.en_US
dc.description.abstractIn 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.description.scholarlevelGraduateen_US
dc.identifier.urihttp://hdl.handle.net/1828/11708
dc.language.isoenen_US
dc.rightsAvailable to the World Wide Weben_US
dc.titleData Cleansing For Training Vehicle Detection Modelsen_US
dc.typeprojecten_US

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