Facial expression recognition by deep learning

Facial expressions have been proven to be a key element in social interaction. With the increasing popularity of artificial intelligence, facial expression systems using various methods have been designed and studied. Traditional machine learning methods such as support vector machines are widely us...

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Main Author: Ding, Hong Wei
Other Authors: Jiang Xudong
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2020
Subjects:
Online Access:https://hdl.handle.net/10356/141030
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1410302023-07-07T17:46:40Z Facial expression recognition by deep learning Ding, Hong Wei Jiang Xudong School of Electrical and Electronic Engineering exdjiang@ntu.edu.sg Engineering::Electrical and electronic engineering Facial expressions have been proven to be a key element in social interaction. With the increasing popularity of artificial intelligence, facial expression systems using various methods have been designed and studied. Traditional machine learning methods such as support vector machines are widely used in this field. However, most of the traditional machine learning methods require a lot of domain expertise as features need to be identified manually. In contrast, deep learning makes use of network layers to learn features hierarchically by itself. Therefore, this project is to study and develop a facial expression recognition system using convolutional neural network. In this report, the way convolutional neural network works, datasets used (the Extended Cohn-Kanade Dataset), neural network used (VGG net), implementation of the system, design of graphical user interface and future works are discussed. Bachelor of Engineering (Electrical and Electronic Engineering) 2020-06-03T07:59:37Z 2020-06-03T07:59:37Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/141030 en application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
spellingShingle Engineering::Electrical and electronic engineering
Ding, Hong Wei
Facial expression recognition by deep learning
description Facial expressions have been proven to be a key element in social interaction. With the increasing popularity of artificial intelligence, facial expression systems using various methods have been designed and studied. Traditional machine learning methods such as support vector machines are widely used in this field. However, most of the traditional machine learning methods require a lot of domain expertise as features need to be identified manually. In contrast, deep learning makes use of network layers to learn features hierarchically by itself. Therefore, this project is to study and develop a facial expression recognition system using convolutional neural network. In this report, the way convolutional neural network works, datasets used (the Extended Cohn-Kanade Dataset), neural network used (VGG net), implementation of the system, design of graphical user interface and future works are discussed.
author2 Jiang Xudong
author_facet Jiang Xudong
Ding, Hong Wei
format Final Year Project
author Ding, Hong Wei
author_sort Ding, Hong Wei
title Facial expression recognition by deep learning
title_short Facial expression recognition by deep learning
title_full Facial expression recognition by deep learning
title_fullStr Facial expression recognition by deep learning
title_full_unstemmed Facial expression recognition by deep learning
title_sort facial expression recognition by deep learning
publisher Nanyang Technological University
publishDate 2020
url https://hdl.handle.net/10356/141030
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