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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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 |
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DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Yu, Zhen Lin Facial expression recognition study based on convolutional neural network |
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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. |
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Lu Shijian |
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Lu Shijian Yu, Zhen Lin |
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Final Year Project |
author |
Yu, Zhen Lin |
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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 |
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2019 |
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http://hdl.handle.net/10356/77044 |
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