Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/72957
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dc.contributor.authorHuang, Danyi
dc.date.accessioned2017-12-15T05:25:26Z
dc.date.available2017-12-15T05:25:26Z
dc.date.issued2017
dc.identifier.urihttp://hdl.handle.net/10356/72957
dc.description.abstractWith the development of technology, Artificial Intelligence (AI) becomes popular and people make use of it to do jobs. But for recyclable materials selection, most of the classification jobs are still done manually. Therefore, this project is aimed to developed a system for classifying materials by using Machine Learning. This paper introduces TensorFlow which is an open source for Machine Learning. By using it, single object is able to be recognized but not for multiple objects in one image. Because of this limitation on TensorFlow, the idea on the combination of Machine Learning and Open Source Computer Vision Library (OpenCV) image processing is also illustrated in this paper. As a result, most of the materials can be recognized and highlighted in an image.en_US
dc.format.extent47 p.en_US
dc.language.isoenen_US
dc.rightsNanyang Technological University
dc.subjectDRNTU::Engineering::Electrical and electronic engineeringen_US
dc.titleMachine learning based classification of recyclable materialsen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorWang Dan Weien_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeBachelor of Engineeringen_US
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Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)
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