Visual recognition using artificial intelligence travel image generation using neural style transfer

With the continuous improvement of the life quality, more and more people start to travel abroad during their holidays. There is no denying that people spend a lot of time buying souvenirs for ourselves and most important, leaving us a special memory. However, people are no longer satisfied with the...

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Main Author: Liu, Tianshu
Other Authors: Yap Kim Hui
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2020
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Online Access:https://hdl.handle.net/10356/139883
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1398832023-07-07T18:41:20Z Visual recognition using artificial intelligence travel image generation using neural style transfer Liu, Tianshu Yap Kim Hui School of Electrical and Electronic Engineering EKHYap@ntu.edu.sg Engineering::Electrical and electronic engineering With the continuous improvement of the life quality, more and more people start to travel abroad during their holidays. There is no denying that people spend a lot of time buying souvenirs for ourselves and most important, leaving us a special memory. However, people are no longer satisfied with the gifts that follow the same pattern. This Travel Image Generation aims to abstract the art style from the famous local painting or photo that people take during their trips and generate the unique travel photos that only belonging to themselves. A beard well lathered is half shaved. The first part of this project focus on the new acknowledges learning. Related literature and lecture notes have been reviewed. Software/library installation and GPU have been well prepared. The second part of this project is to explore the network of the system. Here we used StyleBank [1]. StyleBank consists of multiple convolution filter banks while each filter bank represents one style accordingly. Stylization results will be generated by mapping the StyleBank to the content image. Lastly, the performance of the networks will be tested. We also discussed the difference between stylization results between landscape and portrait. The possible improvement for the whole system will also be mentioned in the report. Bachelor of Engineering (Electrical and Electronic Engineering) 2020-05-22T06:08:11Z 2020-05-22T06:08:11Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/139883 en P3036-182 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
Liu, Tianshu
Visual recognition using artificial intelligence travel image generation using neural style transfer
description With the continuous improvement of the life quality, more and more people start to travel abroad during their holidays. There is no denying that people spend a lot of time buying souvenirs for ourselves and most important, leaving us a special memory. However, people are no longer satisfied with the gifts that follow the same pattern. This Travel Image Generation aims to abstract the art style from the famous local painting or photo that people take during their trips and generate the unique travel photos that only belonging to themselves. A beard well lathered is half shaved. The first part of this project focus on the new acknowledges learning. Related literature and lecture notes have been reviewed. Software/library installation and GPU have been well prepared. The second part of this project is to explore the network of the system. Here we used StyleBank [1]. StyleBank consists of multiple convolution filter banks while each filter bank represents one style accordingly. Stylization results will be generated by mapping the StyleBank to the content image. Lastly, the performance of the networks will be tested. We also discussed the difference between stylization results between landscape and portrait. The possible improvement for the whole system will also be mentioned in the report.
author2 Yap Kim Hui
author_facet Yap Kim Hui
Liu, Tianshu
format Final Year Project
author Liu, Tianshu
author_sort Liu, Tianshu
title Visual recognition using artificial intelligence travel image generation using neural style transfer
title_short Visual recognition using artificial intelligence travel image generation using neural style transfer
title_full Visual recognition using artificial intelligence travel image generation using neural style transfer
title_fullStr Visual recognition using artificial intelligence travel image generation using neural style transfer
title_full_unstemmed Visual recognition using artificial intelligence travel image generation using neural style transfer
title_sort visual recognition using artificial intelligence travel image generation using neural style transfer
publisher Nanyang Technological University
publishDate 2020
url https://hdl.handle.net/10356/139883
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