Lee, Jun Xian (2022) An Offline Handwriting Recognition Model using Convolution Neural Network Algorithms. Final Year Project (Bachelor), Tunku Abdul Rahman University College.
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Abstract
As technology becomes more and more advanced, most paperwork and documents transform from using handwriting for composing documents to using digital documents editing software like Microsoft Word. This documents editing software is easy to use and provides consistency in terms of the readability of text and format of documents. But not everyone is keen to use this software, probably due to the user’s preference, accessibility to the software or even because handwriting is an immediate choice when inspiration comes to mind. Therefore, this proposed project aims to develop a machine learning model that can do proper segmentation from handwritten documents and recognise each segmented handwritten character as accurate as possible. Using this model, handwritten content would be converted into a digital version for further refinement.
Item Type: | Final Year Project |
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Subjects: | Science > Computer Science Technology > Technology (General) |
Faculties: | Faculty of Computing and Information Technology > Bachelor of Computer Science (Honours) in Data Science |
Depositing User: | Library Staff |
Date Deposited: | 17 Aug 2022 02:14 |
Last Modified: | 17 Aug 2022 02:14 |
URI: | https://eprints.tarc.edu.my/id/eprint/22453 |