Facial expression recognition study based on convolutional neural network

The author of this article intends to study facial expression recognition based on deep neural networks. The first part introduces the traditional methods of facial expression recognition. Then introduces the technical development of deep neural network in the field of image recognition. The second...

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Main Author: Yu, Zhen Lin
Other Authors: Lu Shijian
Format: Final Year Project
Language:English
Published: 2019
Subjects:
Online Access:http://hdl.handle.net/10356/77044
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-770442023-03-03T20:34:44Z Facial expression recognition study based on convolutional neural network Yu, Zhen Lin Lu Shijian School of Computer Science and Engineering DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence The author of this article intends to study facial expression recognition based on deep neural networks. The first part introduces the traditional methods of facial expression recognition. Then introduces the technical development of deep neural network in the field of image recognition. The second part discusses the specific implementation of this project. The facial expression recognition was implemented with Python in Pytorch Framework. The comparative analysis was based on 2 convolutional neural networks (VGG19 and Resnet18) implemented on 2 databases. The compare results show Resnet18 achieved better performance than VGG19. After comparison the article will test visualization examples using Resnet18 model. At last the article will discuss recommendations of future work. Bachelor of Engineering (Computer Science) 2019-05-03T07:16:39Z 2019-05-03T07:16:39Z 2019 Final Year Project (FYP) http://hdl.handle.net/10356/77044 en Nanyang Technological University 26 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
spellingShingle DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Yu, Zhen Lin
Facial expression recognition study based on convolutional neural network
description The author of this article intends to study facial expression recognition based on deep neural networks. The first part introduces the traditional methods of facial expression recognition. Then introduces the technical development of deep neural network in the field of image recognition. The second part discusses the specific implementation of this project. The facial expression recognition was implemented with Python in Pytorch Framework. The comparative analysis was based on 2 convolutional neural networks (VGG19 and Resnet18) implemented on 2 databases. The compare results show Resnet18 achieved better performance than VGG19. After comparison the article will test visualization examples using Resnet18 model. At last the article will discuss recommendations of future work.
author2 Lu Shijian
author_facet Lu Shijian
Yu, Zhen Lin
format Final Year Project
author Yu, Zhen Lin
author_sort Yu, Zhen Lin
title Facial expression recognition study based on convolutional neural network
title_short Facial expression recognition study based on convolutional neural network
title_full Facial expression recognition study based on convolutional neural network
title_fullStr Facial expression recognition study based on convolutional neural network
title_full_unstemmed Facial expression recognition study based on convolutional neural network
title_sort facial expression recognition study based on convolutional neural network
publishDate 2019
url http://hdl.handle.net/10356/77044
_version_ 1759857208466604032