Recognizing historical handwritten documents using deep machine learning methods

The paper is devoted to the development and analysis of neural network approaches and methods for solving the problem of handwritten document recognition. To solve this problem, we proposes to use deep neural network models. The issues of configuration and training of the suggested models are considered, and their possible improvements are described and analyzed. The results of a numerical study of all proposed approaches and a comparison of their effectiveness in solving the problem are presented.

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Publication Details

Published
2024-09-30
Primary Topic
Handwritten Text Recognition Techniques
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Recognizing historical handwritten documents using deep machine learning methods

Handwritten Text Recognition Techniques
article

Recognizing historical handwritten documents using deep machine learning methods

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Abstract

The paper is devoted to the development and analysis of neural network approaches and methods for solving the problem of handwritten document recognition. To solve this problem, we proposes to use deep neural network models. The issues of configuration and training of the suggested models are considered, and their possible improvements are described and analyzed. The results of a numerical study of all proposed approaches and a comparison of their effectiveness in solving the problem are presented.

Weatherford College (US)
Openalex Percentile: Top 57%
Handwritten Text Recognition Techniques
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Recognizing historical handwritten documents using deep machine learning methods · (2024) | TGRS Research Map | TGRS