Food recognition application

Singaporeans are facing health problems linking to obesity and type-2 diabetes. In a recent article in 2018, it is estimated that about 8.7% of Singaporeans adults face problems with obesity, while around 8.6% of Singaporeans had type-2 diabetes. It is projected that these numbers will continue to i...

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Main Author: Ke, Jiahao
Other Authors: Shen Zhiqi
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2021
Subjects:
Online Access:https://hdl.handle.net/10356/147941
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1479412021-04-20T00:51:44Z Food recognition application Ke, Jiahao Shen Zhiqi School of Computer Science and Engineering Zhang Yunfang ZQShen@ntu.edu.sg Engineering::Computer science and engineering Singaporeans are facing health problems linking to obesity and type-2 diabetes. In a recent article in 2018, it is estimated that about 8.7% of Singaporeans adults face problems with obesity, while around 8.6% of Singaporeans had type-2 diabetes. It is projected that these numbers will continue to increase. One of the biggest reasons for the above is Singaporean overconsumption of unhealthy food [1]. Thus, there needs to be a solution to help Singaporean keep track of their daily ingestion of food and allow stronger awareness of healthier food alternatives. The objective of this project is to build a mobile application system that helps users keep track of their meals and encourage healthier diets. The application will allow users to take a photo of their meal using the application. The application will then recognize the type of food object(s) in the photo and feedback the user with information of each food object including the calories and nutrients. The user will be able to see a breakdown of the total consumption and nutrition values, compared to the recommended level according to the user’s portfolio Bachelor of Engineering (Computer Science) 2021-04-16T07:53:19Z 2021-04-16T07:53:19Z 2021 Final Year Project (FYP) Ke, J. (2021). Food recognition application. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/147941 https://hdl.handle.net/10356/147941 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::Computer science and engineering
spellingShingle Engineering::Computer science and engineering
Ke, Jiahao
Food recognition application
description Singaporeans are facing health problems linking to obesity and type-2 diabetes. In a recent article in 2018, it is estimated that about 8.7% of Singaporeans adults face problems with obesity, while around 8.6% of Singaporeans had type-2 diabetes. It is projected that these numbers will continue to increase. One of the biggest reasons for the above is Singaporean overconsumption of unhealthy food [1]. Thus, there needs to be a solution to help Singaporean keep track of their daily ingestion of food and allow stronger awareness of healthier food alternatives. The objective of this project is to build a mobile application system that helps users keep track of their meals and encourage healthier diets. The application will allow users to take a photo of their meal using the application. The application will then recognize the type of food object(s) in the photo and feedback the user with information of each food object including the calories and nutrients. The user will be able to see a breakdown of the total consumption and nutrition values, compared to the recommended level according to the user’s portfolio
author2 Shen Zhiqi
author_facet Shen Zhiqi
Ke, Jiahao
format Final Year Project
author Ke, Jiahao
author_sort Ke, Jiahao
title Food recognition application
title_short Food recognition application
title_full Food recognition application
title_fullStr Food recognition application
title_full_unstemmed Food recognition application
title_sort food recognition application
publisher Nanyang Technological University
publishDate 2021
url https://hdl.handle.net/10356/147941
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