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dc.contributor.authorQiu, Liangdongen_US
dc.identifier.citationQiu, L. (2022). Face recognition based on PCA and LDA. Final Year Project (FYP), Nanyang Technological University, Singapore.
dc.description.abstractWith the rapid development of new technologies such as cloud computing, big data analysis, and artificial intelligence (AI), machine learning has quickly become the focus of scientific research. Under the background of new ideas, machine learning has played a very important role in the industrial production of human-computer interaction. These include areas such as health inspection, automated manufacturing, temperature prediction, safety design, safety design and market assessment. The birth of new algorithms and the improvement of algorithm performance are still important challenges for machine learning. Face recognition is one of the most prominent abilities of computer-human vision, and its research includes pattern recognition technology, image processing methods, physiology, psychology, and cognitive computer science. It has close relationship with identification methods which has deep basement on other biometric data and the field of computer human interaction with computer perception. Using machine learning algorithms to solve face recognition problems is a hot topic for research. In this project, the technical research is mainly focused on using two different machine learning techniques (PCA and LDA) to realize the face recognition function of the computer, the results show that compared with the PCA model, the LDA+PCA model has wider room for improvement.en_US
dc.publisherNanyang Technological Universityen_US
dc.subjectEngineering::Electrical and electronic engineeringen_US
dc.titleFace recognition based on PCA and LDAen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorJiang Xudongen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeBachelor of Engineering (Electrical and Electronic Engineering)en_US
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Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)
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