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http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/9933
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DC Field | Value | Language |
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dc.contributor.author | Tripathi, Samanvaya | - |
dc.contributor.author | Jindal, Himanshu [Guided by] | - |
dc.date.accessioned | 2023-09-12T12:23:57Z | - |
dc.date.available | 2023-09-12T12:23:57Z | - |
dc.date.issued | 2023 | - |
dc.identifier.uri | http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/9933 | - |
dc.description | Enrolment No. 191284 | en_US |
dc.description.abstract | Handwritten mathematical expressions are a significant part of many research fields, consisting of engineering, education, and science. The prevalent availability of powerful computational touch-screen appliances, like the modern emergence of deep neural networks as high-quality sequence recognition models, result in the widespread adoption of online recognition of handwritten mathematical expressions. A deeper study and improvement of such technologies is necessary to address the current challenges posed by the extensive usage of distance learning, and remote work due to the world pandemic. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | Jaypee University of Information Technology, Solan, H.P. | en_US |
dc.subject | Convolutional neural networks | en_US |
dc.subject | Mathematical expressions | en_US |
dc.title | Handwritten Mathematical Expression Recognition | en_US |
dc.type | Project Report | en_US |
Appears in Collections: | B.Tech. Project Reports |
Files in This Item:
File | Description | Size | Format | |
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Handwritten Mathematical Expression Recognition.pdf | 1.99 MB | Adobe PDF | View/Open |
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