Handwritten mathematical expression recognition : ScanIt a web based A\application

With the increasing use of computational devices in our everyday lives, more and more tasks have transitioned to an easier methodology, using these devices. However, this is not the case for every single task. Some, like inputting mathematical expressions, have become even more tedious than they wer...

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Main Author: Sriram, Pranav
Other Authors: Chia Liang Tien, Clement
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2021
Subjects:
Online Access:https://hdl.handle.net/10356/148098
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1480982021-04-23T13:15:00Z Handwritten mathematical expression recognition : ScanIt a web based A\application Sriram, Pranav Chia Liang Tien, Clement Loke Yuan Ren School of Computer Science and Engineering yrloke@ntu.edu.sg, ASLTCHIA@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision With the increasing use of computational devices in our everyday lives, more and more tasks have transitioned to an easier methodology, using these devices. However, this is not the case for every single task. Some, like inputting mathematical expressions, have become even more tedious than they were to write out by hand. The goal of this project was to develop a web-based application that can help decrease the arduous nature of this task. The proposed solution implements a client-server architecture in conjunction with a strong convolutional neural network to produce an accessible and intuitive web-based application that accepts user images and returns the LaTeX notation detected. To implement this system, these tasks were conducted: - A literature review and research to determine the optimal model to be used for this use case. - Ported the model into a Flask app, which can be accessed via an API call. - Designed and Developed a user interface through HTML5, CSS and Bootstrap, that follows Schneiderman’s 8 golden rules of a good interface. - Developed a backend server via Node.JS and Express that seamlessly controls the logic and routing of the web application. - Made use of database system MongoDB to store schemas necessary for the application. - Used cloud SaaS provider Cloudinary to host user uploaded images. - Saves user submissions such that they can be accessible anytime, anywhere, and provides options to edit in the case of errors. - Conduct testing along the development process to ensure that any inconsistencies and bugs are eliminated as soon as they are discovered. Through these tasks, the goal of the project was achieved, and initial User Acceptance Testing has provided positive feedback.   Bachelor of Engineering (Computer Science) 2021-04-23T13:14:59Z 2021-04-23T13:14:59Z 2021 Final Year Project (FYP) Sriram, P. (2021). Handwritten mathematical expression recognition : ScanIt a web based A\application. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/148098 https://hdl.handle.net/10356/148098 en SCSE20-0083 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::Computing methodologies::Image processing and computer vision
spellingShingle Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Sriram, Pranav
Handwritten mathematical expression recognition : ScanIt a web based A\application
description With the increasing use of computational devices in our everyday lives, more and more tasks have transitioned to an easier methodology, using these devices. However, this is not the case for every single task. Some, like inputting mathematical expressions, have become even more tedious than they were to write out by hand. The goal of this project was to develop a web-based application that can help decrease the arduous nature of this task. The proposed solution implements a client-server architecture in conjunction with a strong convolutional neural network to produce an accessible and intuitive web-based application that accepts user images and returns the LaTeX notation detected. To implement this system, these tasks were conducted: - A literature review and research to determine the optimal model to be used for this use case. - Ported the model into a Flask app, which can be accessed via an API call. - Designed and Developed a user interface through HTML5, CSS and Bootstrap, that follows Schneiderman’s 8 golden rules of a good interface. - Developed a backend server via Node.JS and Express that seamlessly controls the logic and routing of the web application. - Made use of database system MongoDB to store schemas necessary for the application. - Used cloud SaaS provider Cloudinary to host user uploaded images. - Saves user submissions such that they can be accessible anytime, anywhere, and provides options to edit in the case of errors. - Conduct testing along the development process to ensure that any inconsistencies and bugs are eliminated as soon as they are discovered. Through these tasks, the goal of the project was achieved, and initial User Acceptance Testing has provided positive feedback.  
author2 Chia Liang Tien, Clement
author_facet Chia Liang Tien, Clement
Sriram, Pranav
format Final Year Project
author Sriram, Pranav
author_sort Sriram, Pranav
title Handwritten mathematical expression recognition : ScanIt a web based A\application
title_short Handwritten mathematical expression recognition : ScanIt a web based A\application
title_full Handwritten mathematical expression recognition : ScanIt a web based A\application
title_fullStr Handwritten mathematical expression recognition : ScanIt a web based A\application
title_full_unstemmed Handwritten mathematical expression recognition : ScanIt a web based A\application
title_sort handwritten mathematical expression recognition : scanit a web based a\application
publisher Nanyang Technological University
publishDate 2021
url https://hdl.handle.net/10356/148098
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