Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
Automatic Recognition of Historical Documents of the Beginning of the 20th Century in Russian. / Barakhnin, Vladimir; Gudkov, Stepan.
2025 IEEE XVII International Scientific and Technical Conference on Actual Problems of Electronic Instrument Engineering (APEIE). Institute of Electrical and Electronics Engineers Inc., 2025. p. 1-4.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
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TY - GEN
T1 - Automatic Recognition of Historical Documents of the Beginning of the 20th Century in Russian
AU - Barakhnin, Vladimir
AU - Gudkov, Stepan
N1 - Conference code: 17
PY - 2025/11/18
Y1 - 2025/11/18
N2 - The large number of undeciphered handwritten historical documents stored in archives forces historians to precede the study and introduction of these documents into scientific circulation by manually deciphering them – a very labor-intensive process. The use of information technology makes it possible to automate this process. The work is aimed at creating a system for automatic recognition of books of decisions of volost courts based on a hybrid approach: neural network methods for recognizing handwritten text and linguistic analysis methods for correcting recognition errors. The paper examines the development of one of the system modules: a letter recognizer. An ensemble approach based on convolutional neural networks is used, which allows achieving an F1-score of 75.1%. The first paragraph – the introduction – sets out the problem, the second provides an analysis of the applicability of existing recognition systems to this problem, and the third describes the development of a specialized system for recognizing books of decisions of volost courts.
AB - The large number of undeciphered handwritten historical documents stored in archives forces historians to precede the study and introduction of these documents into scientific circulation by manually deciphering them – a very labor-intensive process. The use of information technology makes it possible to automate this process. The work is aimed at creating a system for automatic recognition of books of decisions of volost courts based on a hybrid approach: neural network methods for recognizing handwritten text and linguistic analysis methods for correcting recognition errors. The paper examines the development of one of the system modules: a letter recognizer. An ensemble approach based on convolutional neural networks is used, which allows achieving an F1-score of 75.1%. The first paragraph – the introduction – sets out the problem, the second provides an analysis of the applicability of existing recognition systems to this problem, and the third describes the development of a specialized system for recognizing books of decisions of volost courts.
KW - оптическое распознавание символов
KW - исторические документы
KW - нейронные сети
KW - волостные суды
KW - извлечение текста
KW - optical character recognition
KW - historical documents
KW - neural networks
KW - volost courts
KW - text extraction
UR - https://www.scopus.com/pages/publications/105031769826
U2 - 10.1109/APEIE66761.2025.11289354
DO - 10.1109/APEIE66761.2025.11289354
M3 - Conference contribution
SN - 979-8-3315-5917-5
SP - 1
EP - 4
BT - 2025 IEEE XVII International Scientific and Technical Conference on Actual Problems of Electronic Instrument Engineering (APEIE)
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2025 IEEE XVII International Scientific and Technical Conference on Actual Problems of Electronic Instrument Engineering
Y2 - 14 November 2025 through 16 November 2025
ER -
ID: 75609441