Developing a seq2seq neural network using visual attention to transform mathematical expressions from images to LaTeX.

The paper presents the methods of development and the results of research on the effectiveness of the seq2seq neural network architecture using Visual Attention mechanism to solve the im2latex problem. The essence of the task is to create a neural network capable of converting an image with mathemat...

Full description

Saved in:
Bibliographic Details
Main Authors: P. A. Vyaznikov, I. D. Kotilevets
Format: Article
Language:Russian
Published: Educational institution «Belarusian State University of Informatics and Radioelectronics» 2022-01-01
Series:Doklady Belorusskogo gosudarstvennogo universiteta informatiki i radioèlektroniki
Subjects:
Online Access:https://doklady.bsuir.by/jour/article/view/3243
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849336086692626432
author P. A. Vyaznikov
I. D. Kotilevets
author_facet P. A. Vyaznikov
I. D. Kotilevets
author_sort P. A. Vyaznikov
collection DOAJ
description The paper presents the methods of development and the results of research on the effectiveness of the seq2seq neural network architecture using Visual Attention mechanism to solve the im2latex problem. The essence of the task is to create a neural network capable of converting an image with mathematical expressions into a similar expression in the LaTeX markup language. This problem belongs to the Image Captioning type: the neural network scans the image and, based on the extracted features, generates a description in natural language. The proposed solution uses the seq2seq architecture, which contains the Encoder and Decoder mechanisms, as well as Bahdanau Attention. A series of experiments was conducted on training and measuring the effectiveness of several neural network models.
format Article
id doaj-art-eae422b593bf4dfe868c097e41fa910a
institution Kabale University
issn 1729-7648
language Russian
publishDate 2022-01-01
publisher Educational institution «Belarusian State University of Informatics and Radioelectronics»
record_format Article
series Doklady Belorusskogo gosudarstvennogo universiteta informatiki i radioèlektroniki
spelling doaj-art-eae422b593bf4dfe868c097e41fa910a2025-08-20T03:45:06ZrusEducational institution «Belarusian State University of Informatics and Radioelectronics»Doklady Belorusskogo gosudarstvennogo universiteta informatiki i radioèlektroniki1729-76482022-01-01198404410.35596/1729-7648-2021-19-8-40-441761Developing a seq2seq neural network using visual attention to transform mathematical expressions from images to LaTeX.P. A. Vyaznikov0I. D. Kotilevets1MIREA – Russian Technological UniversityMIREA – Russian Technological UniversityThe paper presents the methods of development and the results of research on the effectiveness of the seq2seq neural network architecture using Visual Attention mechanism to solve the im2latex problem. The essence of the task is to create a neural network capable of converting an image with mathematical expressions into a similar expression in the LaTeX markup language. This problem belongs to the Image Captioning type: the neural network scans the image and, based on the extracted features, generates a description in natural language. The proposed solution uses the seq2seq architecture, which contains the Encoder and Decoder mechanisms, as well as Bahdanau Attention. A series of experiments was conducted on training and measuring the effectiveness of several neural network models.https://doklady.bsuir.by/jour/article/view/3243im2latexseq2seqnlpneural network
spellingShingle P. A. Vyaznikov
I. D. Kotilevets
Developing a seq2seq neural network using visual attention to transform mathematical expressions from images to LaTeX.
Doklady Belorusskogo gosudarstvennogo universiteta informatiki i radioèlektroniki
im2latex
seq2seq
nlp
neural network
title Developing a seq2seq neural network using visual attention to transform mathematical expressions from images to LaTeX.
title_full Developing a seq2seq neural network using visual attention to transform mathematical expressions from images to LaTeX.
title_fullStr Developing a seq2seq neural network using visual attention to transform mathematical expressions from images to LaTeX.
title_full_unstemmed Developing a seq2seq neural network using visual attention to transform mathematical expressions from images to LaTeX.
title_short Developing a seq2seq neural network using visual attention to transform mathematical expressions from images to LaTeX.
title_sort developing a seq2seq neural network using visual attention to transform mathematical expressions from images to latex
topic im2latex
seq2seq
nlp
neural network
url https://doklady.bsuir.by/jour/article/view/3243
work_keys_str_mv AT pavyaznikov developingaseq2seqneuralnetworkusingvisualattentiontotransformmathematicalexpressionsfromimagestolatex
AT idkotilevets developingaseq2seqneuralnetworkusingvisualattentiontotransformmathematicalexpressionsfromimagestolatex