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|Title:||Deep learning algorithms and applications||Authors:||Santoso, Yosua Nathanael||Keywords:||DRNTU::Engineering||Issue Date:||2018||Abstract:||Deep learning architecture algorithms have been extensively developed and applied to various applications. The techniques have successfully improved the performance of difficult computer tasks such as computer vision, natural language processing, and speech recognition. This project aims to apply one of the well-known deep learning algorithms, Convolutional Neural Network to detect student engagement which is believed to be an important factor for learning outcome. The input data which is in the form of frontal videos of students watching online recording were collected and pre-processed before being fed into the seven layers of CNN. The trained model reached a considered decent accuracy result. Some applications utilizing the trained model such as real-time engagement detection and graphical representation of student engagement are also introduced in this project.||URI:||http://hdl.handle.net/10356/75195||Rights:||Nanyang Technological University||Fulltext Permission:||restricted||Fulltext Availability:||With Fulltext|
|Appears in Collections:||EEE Student Reports (FYP/IA/PA/PI)|
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