Visual search using deep learning : group emotion recognition using deep learning
Deep learning is a massive research field due to its possible imitation of human behaviours to automate and speed up processes. With a sea of applications such as image recognition, natural language processing and autonomous vehicles, this project would focus on the group emotional field. Other...
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2020
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sg-ntu-dr.10356-1387662023-07-07T18:22:49Z Visual search using deep learning : group emotion recognition using deep learning Lim, Regina Qing Xia Yap Kim Hui School of Electrical and Electronic Engineering EKHYap@ntu.edu.sg Engineering::Electrical and electronic engineering Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Deep learning is a massive research field due to its possible imitation of human behaviours to automate and speed up processes. With a sea of applications such as image recognition, natural language processing and autonomous vehicles, this project would focus on the group emotional field. Other than communicating through words and actions, emotions could also convey messages. This project aims to train a deep learning network to classify group emotions inferred from images as negative, neutral or positive. The objective of this project is to work towards text-based image retrieval for a personal gallery. A dataset was requested online to train two deep learning architecture models, VGG and ResNet. These trained models would be able to recognize different features from images and then classify them. Results from the models would be combined using an ensemble to have the final classification. A test dataset, which mimics a personal gallery, was created to test the performance of the ensemble network. Using ablation studies, there is further analysis of the ensemble network to identify the best model which would be selected to construct a GUI application. There would also be experimental results and discussions that would be shown in this report. Bachelor of Engineering (Electrical and Electronic Engineering) 2020-05-12T08:18:21Z 2020-05-12T08:18:21Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/138766 en A3288-191 application/pdf Nanyang Technological University |
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Engineering::Electrical and electronic engineering Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Lim, Regina Qing Xia Visual search using deep learning : group emotion recognition using deep learning |
description |
Deep learning is a massive research field due to its possible imitation of human
behaviours to automate and speed up processes. With a sea of applications such as
image recognition, natural language processing and autonomous vehicles, this project
would focus on the group emotional field.
Other than communicating through words and actions, emotions could also convey
messages. This project aims to train a deep learning network to classify group
emotions inferred from images as negative, neutral or positive. The objective of this
project is to work towards text-based image retrieval for a personal gallery.
A dataset was requested online to train two deep learning architecture models, VGG
and ResNet. These trained models would be able to recognize different features from
images and then classify them. Results from the models would be combined using an
ensemble to have the final classification. A test dataset, which mimics a personal
gallery, was created to test the performance of the ensemble network. Using ablation
studies, there is further analysis of the ensemble network to identify the best model
which would be selected to construct a GUI application. There would also be
experimental results and discussions that would be shown in this report. |
author2 |
Yap Kim Hui |
author_facet |
Yap Kim Hui Lim, Regina Qing Xia |
format |
Final Year Project |
author |
Lim, Regina Qing Xia |
author_sort |
Lim, Regina Qing Xia |
title |
Visual search using deep learning : group emotion recognition using deep learning |
title_short |
Visual search using deep learning : group emotion recognition using deep learning |
title_full |
Visual search using deep learning : group emotion recognition using deep learning |
title_fullStr |
Visual search using deep learning : group emotion recognition using deep learning |
title_full_unstemmed |
Visual search using deep learning : group emotion recognition using deep learning |
title_sort |
visual search using deep learning : group emotion recognition using deep learning |
publisher |
Nanyang Technological University |
publishDate |
2020 |
url |
https://hdl.handle.net/10356/138766 |
_version_ |
1772826035247644672 |