iReceipt : an intelligent expenses tracker, based on receipt analysis and machine learning (A)
Tracking expenses has always been a daunting and tedious task. Many people do not have the habit of tracking expenses simply because it is not worth the effort to take note of every purchase and record it down just to know how much one spends. However, research has shown that tracking one’s expenses...
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2020
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sg-ntu-dr.10356-1401632023-07-07T18:49:21Z iReceipt : an intelligent expenses tracker, based on receipt analysis and machine learning (A) Young, Ying Jie Wesley Tan Chee Wah School of Electrical and Electronic Engineering wesleytan@ntu.edu.sg Engineering::Electrical and electronic engineering Tracking expenses has always been a daunting and tedious task. Many people do not have the habit of tracking expenses simply because it is not worth the effort to take note of every purchase and record it down just to know how much one spends. However, research has shown that tracking one’s expenses can allow the individual to become more aware and careful on his/her future purchases as well as improve the person’s memory and thinking. In this Final Year Project (FYP), we propose to create a mobile application using the technology of Optical Character Recognition (OCR) to simplify the task of tracking expenses. Using the application, a user simply has to upload an image of his/her spending receipt and the necessary information such as the Merchant Name, Category of Spending and Spending Amount will be stored for tracking purposes. This way, users do not have to manually key in every amount for every purchase they have made but can just simply take a photograph of their receipts. In addition, users will be able to see their receipt images as well as visual representations of their spending in the form of a bar graph as well as a pie chart to better understand how much they should spend and what they should spend less on. Bachelor of Engineering (Electrical and Electronic Engineering) 2020-05-27T03:22:02Z 2020-05-27T03:22:02Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/140163 en A3004-191 application/pdf Nanyang Technological University |
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Engineering::Electrical and electronic engineering Young, Ying Jie iReceipt : an intelligent expenses tracker, based on receipt analysis and machine learning (A) |
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Tracking expenses has always been a daunting and tedious task. Many people do not have the habit of tracking expenses simply because it is not worth the effort to take note of every purchase and record it down just to know how much one spends. However, research has shown that tracking one’s expenses can allow the individual to become more aware and careful on his/her future purchases as well as improve the person’s memory and thinking. In this Final Year Project (FYP), we propose to create a mobile application using the technology of Optical Character Recognition (OCR) to simplify the task of tracking expenses. Using the application, a user simply has to upload an image of his/her spending receipt and the necessary information such as the Merchant Name, Category of Spending and Spending Amount will be stored for tracking purposes. This way, users do not have to manually key in every amount for every purchase they have made but can just simply take a photograph of their receipts. In addition, users will be able to see their receipt images as well as visual representations of their spending in the form of a bar graph as well as a pie chart to better understand how much they should spend and what they should spend less on. |
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Wesley Tan Chee Wah |
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Wesley Tan Chee Wah Young, Ying Jie |
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Final Year Project |
author |
Young, Ying Jie |
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Young, Ying Jie |
title |
iReceipt : an intelligent expenses tracker, based on receipt analysis and machine learning (A) |
title_short |
iReceipt : an intelligent expenses tracker, based on receipt analysis and machine learning (A) |
title_full |
iReceipt : an intelligent expenses tracker, based on receipt analysis and machine learning (A) |
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iReceipt : an intelligent expenses tracker, based on receipt analysis and machine learning (A) |
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iReceipt : an intelligent expenses tracker, based on receipt analysis and machine learning (A) |
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ireceipt : an intelligent expenses tracker, based on receipt analysis and machine learning (a) |
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Nanyang Technological University |
publishDate |
2020 |
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https://hdl.handle.net/10356/140163 |
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1772827592571748352 |