Optical character recognition with neural networks
XXI century is the age of global automation and digitization. There is high demand for optical recognition software, including character recognition. There are different approaches in solution optical recognition problem. Some of them based on classical feature extraction methods. Other based on mac...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Al-Farabi Kazakh National University
2019-01-01
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| Series: | Вестник КазНУ. Серия математика, механика, информатика |
| Subjects: | |
| Online Access: | https://bm.kaznu.kz/index.php/kaznu/article/view/572/460 |
| _version_ | 1818649189399134208 |
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| author | Aidarbek Shalakhmetov Sanzhar Aubakirov |
| author_facet | Aidarbek Shalakhmetov Sanzhar Aubakirov |
| author_sort | Aidarbek Shalakhmetov |
| collection | DOAJ |
| description | XXI century is the age of global automation and digitization. There is high demand for optical recognition software, including character recognition. There are different approaches in solution optical recognition problem. Some of them based on classical feature extraction methods. Other based on machine learning algorithms. In this work, we observed related works in machine learning field and propose the plan for further research. The work relies on two research studies that describe basics and fundamentals of machine learning. These researches include various experiments in this field. We tried to repeat these experiments to get acquainted with methods and techniques and to identify key features that are affecting on optical character recognition process. We analyzed two main architectural structures: multilayer perceptron and convolutional neural network. In conclusion, we learned key points of machine learning techniques and composed our own strategy for further researches. Further work will cover researches and experiments on performance of several architectures. In addition, we observed latest tools, software programs and environments for the most convenient way to organize implementation process. |
| first_indexed | 2024-12-17T01:30:22Z |
| format | Article |
| id | doaj.art-4e4c120a48a54440882f80306b4b3de0 |
| institution | Directory Open Access Journal |
| issn | 1563-0277 2617-4871 |
| language | English |
| last_indexed | 2024-12-17T01:30:22Z |
| publishDate | 2019-01-01 |
| publisher | Al-Farabi Kazakh National University |
| record_format | Article |
| series | Вестник КазНУ. Серия математика, механика, информатика |
| spelling | doaj.art-4e4c120a48a54440882f80306b4b3de02022-12-21T22:08:35ZengAl-Farabi Kazakh National UniversityВестник КазНУ. Серия математика, механика, информатика1563-02772617-48712019-01-0110042841https://doi.org/10.26577/JMMCS-2018-4-572Optical character recognition with neural networksAidarbek Shalakhmetov0Sanzhar Aubakirov1University of International BusinessUniversity of International BusinessXXI century is the age of global automation and digitization. There is high demand for optical recognition software, including character recognition. There are different approaches in solution optical recognition problem. Some of them based on classical feature extraction methods. Other based on machine learning algorithms. In this work, we observed related works in machine learning field and propose the plan for further research. The work relies on two research studies that describe basics and fundamentals of machine learning. These researches include various experiments in this field. We tried to repeat these experiments to get acquainted with methods and techniques and to identify key features that are affecting on optical character recognition process. We analyzed two main architectural structures: multilayer perceptron and convolutional neural network. In conclusion, we learned key points of machine learning techniques and composed our own strategy for further researches. Further work will cover researches and experiments on performance of several architectures. In addition, we observed latest tools, software programs and environments for the most convenient way to organize implementation process.https://bm.kaznu.kz/index.php/kaznu/article/view/572/460ocrneural networkconvolutional neural networks |
| spellingShingle | Aidarbek Shalakhmetov Sanzhar Aubakirov Optical character recognition with neural networks Вестник КазНУ. Серия математика, механика, информатика ocr neural network convolutional neural networks |
| title | Optical character recognition with neural networks |
| title_full | Optical character recognition with neural networks |
| title_fullStr | Optical character recognition with neural networks |
| title_full_unstemmed | Optical character recognition with neural networks |
| title_short | Optical character recognition with neural networks |
| title_sort | optical character recognition with neural networks |
| topic | ocr neural network convolutional neural networks |
| url | https://bm.kaznu.kz/index.php/kaznu/article/view/572/460 |
| work_keys_str_mv | AT aidarbekshalakhmetov opticalcharacterrecognitionwithneuralnetworks AT sanzharaubakirov opticalcharacterrecognitionwithneuralnetworks |