Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/140278
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dc.contributor.authorWang, Yuchenen_US
dc.date.accessioned2020-05-27T12:05:02Z-
dc.date.available2020-05-27T12:05:02Z-
dc.date.issued2020-
dc.identifier.urihttps://hdl.handle.net/10356/140278-
dc.description.abstractWith the fast-developing technology, the application using emerging technology is replacing some application using conventional one. Radar for surveillance application can be one of them. With the help of machine learning and big data, it can reach a very high recognition and classification rate. This project is aimed to develop a relatively low-cost radar system with machine learning and mainly focus on improving the recognition accuracy. The report summarizes the knowledge of 24GHz radar working principle, signal processing and image processing, compares the recognition accuracy result with different machine learning result. As a result, the radar system can reach up to 98% recognition accuracy with limited training data.en_US
dc.language.isoenen_US
dc.publisherNanyang Technological Universityen_US
dc.relationP3048-182en_US
dc.subjectEngineering::Electrical and electronic engineeringen_US
dc.titleMillimeter wave radar with machine intelligence for home surveillance applicationsen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorLU Yilongen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeBachelor of Engineering (Electrical and Electronic Engineering)en_US
dc.contributor.supervisoremailEYLU@ntu.edu.sgen_US
item.grantfulltextrestricted-
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Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)
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