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dc.contributor.authorYap, Jinson
dc.description.abstractThe current rapid development of technology and applications of object detection has always been an important Image recognition is a research area that is ongoing and is always challenging to task it in computer vision in many areas. There is a large array of different object categories, hence we need to train. Object recognition for new object in datasets requires more time to process to those classifiers, as it needs to be trained to allow the database to increase. However, there are existing file that have datasets like TensorFlow. This project proposed to use this content to implement on app to enhance the children’s education through technology. Education is key to development in kids learning ability and with this project it will enhance the kids learning. This project labels each individual elements of an image into its own category regions and provide a label for each object. The of methods extracting features from an annotated image are store into database containing about 100000 images and 200 objects. Every parameter has its own futures that can be explored, and analysed to achieved the best accuracy.en_US
dc.format.extent52 p.en_US
dc.rightsNanyang Technological University
dc.subjectDRNTU::Engineering::Electrical and electronic engineeringen_US
dc.titleHarnessing object detection for learningen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorWang Hanen_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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