Please use this identifier to cite or link to this item: http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/9933
Title: Handwritten Mathematical Expression Recognition
Authors: Tripathi, Samanvaya
Jindal, Himanshu [Guided by]
Keywords: Convolutional neural networks
Mathematical expressions
Issue Date: 2023
Publisher: Jaypee University of Information Technology, Solan, H.P.
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.
Description: Enrolment No. 191284
URI: http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/9933
Appears in Collections:B.Tech. Project Reports

Files in This Item:
File Description SizeFormat 
Handwritten Mathematical Expression Recognition.pdf1.99 MBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.