<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.3 20210610//EN" "JATS-journalpublishing1-3.dtd">
<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">sudexpert</journal-id><journal-title-group><journal-title xml:lang="ru">Теория и практика судебной экспертизы</journal-title><trans-title-group xml:lang="en"><trans-title>Theory and Practice of Forensic Science</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">1819-2785</issn><issn pub-type="epub">2587-7275</issn><publisher><publisher-name>The Russian Federal Centre of Forensic Science</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.30764/1819-2785-2025-1-44-65</article-id><article-id custom-type="elpub" pub-id-type="custom">sudexpert-865</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>СУДЕБНАЯ ЭКСПЕРТИЗА ЗА РУБЕЖОМ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>INTERNATIONAL PERSPECTIVES IN FORENSIC SCIENCE</subject></subj-group></article-categories><title-group><article-title>Использование искусственных нейронных сетей для решения задач судебно-почерковедческой экспертизы: анализ зарубежного опыта</article-title><trans-title-group xml:lang="en"><trans-title>Using Artificial Neural Networks for Solving Forensic Handwriting Examination Problems: Foreign Experience Analysis</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-1391-4050</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Мищук</surname><given-names>В. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Mishchuk</surname><given-names>V. A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Мищук Всеволод Александрович – аспирант кафедры судебно-экспертной деятельности Юридического института </p><p>Москва 117198</p></bio><bio xml:lang="en"><p>Mishchuk Vsevolod Aleksandrovich – PhD student of the Department of Forensic Science, Institute of Law</p><p>Moscow 117198</p></bio><email xlink:type="simple">seva.mi.112@yandex.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>ФГАОУ ВО «Российский университет дружбы народов имени Патриса Лумумбы</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Peoples’ Friendship University of Russia named after Patrice Lumumba</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2025</year></pub-date><pub-date pub-type="epub"><day>18</day><month>04</month><year>2025</year></pub-date><volume>20</volume><issue>1</issue><fpage>44</fpage><lpage>65</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Мищук В.А., 2025</copyright-statement><copyright-year>2025</copyright-year><copyright-holder xml:lang="ru">Мищук В.А.</copyright-holder><copyright-holder xml:lang="en">Mishchuk V.A.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://www.tipse.ru/jour/article/view/865">https://www.tipse.ru/jour/article/view/865</self-uri><abstract><p>В работе исследуется зарубежный опыт применения искусственных нейронных сетей (ИНС) в судебно-почерковедческой экспертизе. На фоне активного внедрения ИНС в различные сферы общественной жизни наблюдается повышенное внимание к теме интеграции этой технологии в судебно-экспертную деятельность. Особенно остро стоит вопрос применения нейросетей в судебно-почерковедческой экспертизе, поскольку, по мнению некоторых ученых и юристов, их использование может значительно повысить объективность почерковедческих исследований.</p><p>В статье приведен краткий обзор истории и современных тенденций применения компьютерных технологий в исследовании почерка, рассмотрена связь криминалистики и биометрии в этой области, а также их взаимное влияние, особенно в зарубежной практике экспертизы почерка. Приведены примеры современных успешных проектов и экспериментов, демонстрирующих эффективное использование нейронных сетей для идентификации и верификации человека по его почерку. Обсуждены перспективы развития этого направления и выявлены ключевые проблемы, которые, по мнению автора, в настоящее время препятствуют интеграции нейросетей в судебнопочерковедческую экспертизу.</p></abstract><trans-abstract xml:lang="en"><p>This paper studies the foreign experience of artificial neural networks (ANN) application in forensic handwriting examination. Given the active ANN implementation in various areas of public life, greater attention is paid to the integration of this technology into forensic activities. According to the opinion of a number of scientists and lawyers the issue of applying neural networks to forensic handwriting examination is particularly acute as they can significantly improve the objectivity of handwriting examinations.</p><p>The article gives a brief overview of history and current developments in computer technology use for handwriting examination as well as the connection and mutual influence of forensics and biometrics in this field which is particularly characteristic of foreign practice of forensic handwriting examination. Furthermore, the author presents examples of successful projects and experiments demonstrating effective use of neural networks to identify and verify an individual by his handwriting. The paper also discusses the prospects of this field and identifies the key challenges hindering, in the author’s opinion, the ANN integration in forensic handwriting examination.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>биометрия</kwd><kwd>зарубежный опыт</kwd><kwd>идентификация человека по почерку</kwd><kwd>искусственные нейронные сети</kwd><kwd>компьютерные технологии</kwd><kwd>судебно-почерковедческая экспертиза</kwd></kwd-group><kwd-group xml:lang="en"><kwd>biometrics</kwd><kwd>foreign experience</kwd><kwd>handwriting identification</kwd><kwd>artificial neural networks (ANN)</kwd><kwd>computing technology</kwd><kwd>forensic handwriting examination</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Hicklin R.A., Eisenhart L., Richetelli N., Miller M.D., Belcastro P. et al. Accuracy and Reliability of Forensic Handwriting Comparisons // Proceedings of the National Academy of Sciences. 2022. Vol. 119. No. 32. https://doi.org/10.1073/pnas.2119944119</mixed-citation><mixed-citation xml:lang="en">Hicklin R.A., Eisenhart L., Richetelli N., Miller M.D., Belcastro P. et al. Accuracy and Reliability of Forensic Handwriting Comparisons. Proceedings of the National Academy of Sciences. 2022. Vol. 119. No. 32. https://doi.org/10.1073/pnas.2119944119</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">Охлупина А.Н. Проблема однозначности выделения признаков подписей и ее влияние на процесс автоматизации экспертных исследований // Алтайский юридический вестник. 2019. № 1 (25). С. 115–120.</mixed-citation><mixed-citation xml:lang="en">Оkhlupina A.N. The Problem of Unambiguous Identification of Signatures and Its Impact on the Automation of Expert Research. Altai Legal Bulletin. 2019. No. 1 (25). P. 115–120. (In Russ.).</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">Scientific Working Group for Forensic Document Examination (SWGDOC). https://swgdoc.org</mixed-citation><mixed-citation xml:lang="en">Scientific Working Group for Forensic Document Examination (SWGDOC). https://swgdoc.org</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">Taylor M., Bishop B., Burkes T., Caligiuri M., Found B. et al. Forensic Handwriting Examination and Human Factors: Improving the Practice Through a Systems Approach // NIST Interagency/Internal Report (NISTIR). 2021. https://doi.org/10.6028/NIST.IR.8282r1</mixed-citation><mixed-citation xml:lang="en">Taylor M., Bishop B., Burkes T., Caligiuri M., Found B. et al. Forensic Handwriting Examination and Human Factors: Improving the Practice Through a Systems Approach. NIST Interagency/Internal Report (NISTIR). 2021. https://doi.org/10.6028/NIST.IR.8282r1</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Best Practice Manual for the Forensic Handwriting Examination. 4th ed. // ENFSI. 2022. https://enfsi.eu/wp-content/uploads/2023/02/BPM-Handwriting-Ed.-4.pdf</mixed-citation><mixed-citation xml:lang="en">Best Practice Manual for the Forensic Handwriting Examination. 4th ed. ENFSI. 2022. https://enfsi.eu/wp-content/uploads/2023/02/BPM-Handwriting-Ed.-4.pdf</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">ГОСТ Р 54412–2019. Информационные технологии. Биометрия. Общие положения и примеры применения. https://files.stroyinf.ru/Data2/1/4293725/4293725565.pdf?ysclid=m82sulc6uq418677385</mixed-citation><mixed-citation xml:lang="en">ISO/IEC TR 24741:2018. Information technology – Biometrics – Overview and application, MOD. https://files.stroyinf.ru/Data2/1/4293725/4293725565.pdf?ysclid=m82sulc6uq418677385</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">Кошманов М.П., Кошманов П.М. Этапы и основные направления внедрения компьютерных технологий в судебное почерковедение и почерковедческую экспертизу // Эксперткриминалист. 2008. № 3. С. 35–40.</mixed-citation><mixed-citation xml:lang="en">Koshmanov M.P., Koshmanov P.M. Stages and Basic Directions of Computer Technologies Implementation in Forensic Handwriting Examination. Forensic Scientist. 2008. No. 3. P. 35–40. (In Russ.).</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">Минаев Ю., Мамаев В. Итоги и перспективы развития биометрических технологий // Системы безопасности. 01.02.2021. https://www.secuteck.ru/articles/itogi-i-perspektivyrazvitiya-biometricheskih-tekhnologij</mixed-citation><mixed-citation xml:lang="en">Minaev Yu., Mamaev V. Results and Prospects of Biometric Technology Development. Security and Safety. 01.02.2021. https://www.secuteck.ru/articles/itogi-i-perspektivyrazvitiya-biometricheskih-tekhnologij</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">Ferguson R.W. Presentation to a Workshop on Promoting the Use of Electronic Payments, Held at the Federal Reserve Bank of Chicago. Chicago, 2000.</mixed-citation><mixed-citation xml:lang="en">Ferguson R.W. Presentation to a Workshop on Promoting the Use of Electronic Payments, Held at the Federal Reserve Bank of Chicago. Chicago, 2000.</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">Potter E.J. Customer Authentication: The Evolution of Signature Verification in Financial Institutions // Journal of Economic Crime Management. 2002. Vol. 1. No. 1. P. 1–19.</mixed-citation><mixed-citation xml:lang="en">Potter E.J. Customer Authentication: The Evolution of Signature Verification in Financial Institutions. Journal of Economic Crime Management. 2002. Vol. 1. No. 1. P. 1–19.</mixed-citation></citation-alternatives></ref><ref id="cit11"><label>11</label><citation-alternatives><mixed-citation xml:lang="ru">Dormehl L. Tracing the History and Evolution of the Stylus // Digital Trends. 04.05.2021. https://www.digitaltrends.com/mobile/evolutionhistory-of-the-stylus/#dt-heading-as-we-may-think</mixed-citation><mixed-citation xml:lang="en">Dormehl L. Tracing the History and Evolution of the Stylus. Digital Trends. 04.05.2021. https://www.digitaltrends.com/mobile/evolutionhistory-of-the-stylus/#dt-heading-as-we-may-think</mixed-citation></citation-alternatives></ref><ref id="cit12"><label>12</label><citation-alternatives><mixed-citation xml:lang="ru">Yoshimura M., Kimura F., Yoshimura I. Experimental Comparison of Two Types of Methods of Writer Identification // IEICE Transactions (1976–1990). 1982. Vol. 65. No. 6. P. 345–352.</mixed-citation><mixed-citation xml:lang="en">Yoshimura M., Kimura F., Yoshimura I. Experimental Comparison of Two Types of Methods of Writer Identification. IEICE Transactions (1976– 1990). 1982. Vol. 65. No. 6. P. 345–352.</mixed-citation></citation-alternatives></ref><ref id="cit13"><label>13</label><citation-alternatives><mixed-citation xml:lang="ru">Nagel R.N., Rosenfeld A. Computer Detection of Freehand Forgeries // IEEE Transactions on Computers. 1977. Vol. C-26. No. 9. P. 895–905. https://doi.org/10.1109/tc.1977.1674937</mixed-citation><mixed-citation xml:lang="en">Nagel R.N., Rosenfeld A. Computer Detection of Freehand Forgeries. IEEE Transactions on Computers. 1977. Vol. C-26. No. 9. P. 895–905. https://doi.org/10.1109/tc.1977.1674937</mixed-citation></citation-alternatives></ref><ref id="cit14"><label>14</label><citation-alternatives><mixed-citation xml:lang="ru">Plamondon R., Lorette G. Automatic Signature Verification and Writer Identification – the State of the Art // Pattern Recognition. 1989. Vol. 22. No. 2. P. 107–131. https://doi.org/10.1016/0031-3203(89)90059-9</mixed-citation><mixed-citation xml:lang="en">Plamondon R., Lorette G. Automatic Signature Verification and Writer Identification – the State of the Art. Pattern Recognition. 1989. Vol. 22. No. 2. P. 107–131. https://doi.org/10.1016/0031-3203(89)90059-9</mixed-citation></citation-alternatives></ref><ref id="cit15"><label>15</label><citation-alternatives><mixed-citation xml:lang="ru">Leclerc F., Plamondon R. Automatic Signature Verification: The State of the Art – 1989–1993 // International Journal of Pattern Recognition and Artificial Intelligence. 1994. Vol. 8. No. 3. P. 643–660. https://doi.org/10.1142/S0218001494000346</mixed-citation><mixed-citation xml:lang="en">Leclerc F., Plamondon R. Automatic Signature Verification: The State of the Art – 1989–1993. International Journal of Pattern Recognition and Artificial Intelligence. 1994. Vol. 8. No. 3. P. 643–660. https://doi.org/10.1142/S0218001494000346</mixed-citation></citation-alternatives></ref><ref id="cit16"><label>16</label><citation-alternatives><mixed-citation xml:lang="ru">Srihari S., Leedham G. Survey of Computer Methods in Forensic Handwritten Document Examination // Proceedings Eleventh International Graphonomics Society Conference. Sccottsdale, 2003. P. 278–281.</mixed-citation><mixed-citation xml:lang="en">Srihari S., Leedham G. Survey of Computer Methods in Forensic Handwritten Document Examination. Proceedings Eleventh International Graphonomics Society Conference. Sccottsdale, 2003. P. 278–281.</mixed-citation></citation-alternatives></ref><ref id="cit17"><label>17</label><citation-alternatives><mixed-citation xml:lang="ru">Sreeraj M., Idicula S.M. A Survey on Writer Identification Schemes // International Journal of Computer Applications. 2011. Vol. 26. No. 2. P. 23–33. https://doi.org/10.5120/3075-4205</mixed-citation><mixed-citation xml:lang="en">Sreeraj M., Idicula S.M. A Survey on Writer Identification Schemes. International Journal of Computer Applications. 2011. Vol. 26. No. 2. P. 23–33. https://doi.org/10.5120/3075-4205</mixed-citation></citation-alternatives></ref><ref id="cit18"><label>18</label><citation-alternatives><mixed-citation xml:lang="ru">Harralson H.H., Miller L.S. Huber and Headrick’s Handwriting Identification: Facts and Fundamentals. 2nd ed. CRC Press, 2017. 442 p. https://doi.org/10.4324/9781315152462</mixed-citation><mixed-citation xml:lang="en">Harralson H.H., Miller L.S. Huber and Headrick’s Handwriting Identification: Facts and Fundamentals. 2nd ed. CRC Press, 2017. 442 p. https://doi.org/10.4324/9781315152462</mixed-citation></citation-alternatives></ref><ref id="cit19"><label>19</label><citation-alternatives><mixed-citation xml:lang="ru">Deviterne-Lapeyre M., Ibrahim S. Interpol Questioned Documents Review 2019–2022 // Forensic Science International: Synergy. 2023. Vol. 6. https://doi.org/10.1016/j.fsisyn.2022.100300</mixed-citation><mixed-citation xml:lang="en">Deviterne-LapeyreM., IbrahimS. Interpol Questioned Documents Review 2019–2022. Forensic Science International: Synergy. 2023. Vol. 6. https://doi.org/10.1016/j.fsisyn.2022.100300</mixed-citation></citation-alternatives></ref><ref id="cit20"><label>20</label><citation-alternatives><mixed-citation xml:lang="ru">Иванов А.И. Биометрическая идентификация личности по динамике подсознательных движений. Пенза: Изд-во Пенз. гос. ун-та, 2000. 187 с.</mixed-citation><mixed-citation xml:lang="en">Ivanov A.I. Biometric Personality Identification Based on Subconscious Movement Dynamics. Penza: Publishing House of Penza State University, 2000. 187 p. (In Russ.).</mixed-citation></citation-alternatives></ref><ref id="cit21"><label>21</label><citation-alternatives><mixed-citation xml:lang="ru">Risinger D.M., Denbeaux M.P., Saks M.J. Exorcism of Ignorance as a Proxy for Rational Knowledge: The Lessons of Handwriting Identification “Expertise” // The University of Pennsylvania Law Review. 1989. Vol. 137. No. 3. P. 731–792. https://doi.org/10.2307/3312276</mixed-citation><mixed-citation xml:lang="en">Risinger D.M., Denbeaux M.P., Saks M.J. Exorcism of Ignorance as a Proxy for Rational Knowledge: The Lessons of Handwriting Identification “Expertise”. The University of Pennsylvania Law Review. 1989. Vol. 137. No. 3. P. 731–792. https://doi.org/10.2307/3312276</mixed-citation></citation-alternatives></ref><ref id="cit22"><label>22</label><citation-alternatives><mixed-citation xml:lang="ru">Crawford M.A. Daubert Standard. Walden University, 2014. 8 p. https://doi.org/10.13140/2.1.2002.2560</mixed-citation><mixed-citation xml:lang="en">Crawford M.A. Daubert Standard. Walden University, 2014. 8 p. https://doi.org/10.13140/2.1.2002.2560</mixed-citation></citation-alternatives></ref><ref id="cit23"><label>23</label><citation-alternatives><mixed-citation xml:lang="ru">United States v. Starzecpyzel, 880 F. Supp. 1027. (S.D.N.Y. 1995) // Justia. U.S. Law. https://law.justia.com/cases/federal/districtcourts/FSupp/880/1027/1408539</mixed-citation><mixed-citation xml:lang="en">United States v. Starzecpyzel, 880 F. Supp. 1027. (S.D.N.Y. 1995) // Justia. U.S. Law. https://law.justia.com/cases/federal/districtcourts/FSupp/880/1027/1408539</mixed-citation></citation-alternatives></ref><ref id="cit24"><label>24</label><citation-alternatives><mixed-citation xml:lang="ru">Strengthening Forensic Science in the United States: a Path Forward. The National Academies Press, 2009. 328 p.</mixed-citation><mixed-citation xml:lang="en">Strengthening Forensic Science in the United States: a Path Forward. The National Academies Press, 2009. 328 p.</mixed-citation></citation-alternatives></ref><ref id="cit25"><label>25</label><citation-alternatives><mixed-citation xml:lang="ru">Robert E. Pettus, Appellant, v. United States, Appellee // FindLaw. https://caselaw.findlaw.com/court/dc-court-of-appeals/1593870.html</mixed-citation><mixed-citation xml:lang="en">Robert E. Pettus, Appellant, v. United States, Appellee // FindLaw. https://caselaw.findlaw.com/court/dc-court-of-appeals/1593870.html</mixed-citation></citation-alternatives></ref><ref id="cit26"><label>26</label><citation-alternatives><mixed-citation xml:lang="ru">Koehler J.J. Intuitive Error Rate Estimates for the Forensic Sciences // Jurimetrics. 2017. Vol. 57. P. 153–168. http://doi.org/10.2139/ssrn.2817443</mixed-citation><mixed-citation xml:lang="en">Koehler J.J. Intuitive Error Rate Estimates for the Forensic Sciences. Jurimetrics. 2017. Vol. 57. P. 153–168. http://doi.org/10.2139/ssrn.2817443</mixed-citation></citation-alternatives></ref><ref id="cit27"><label>27</label><citation-alternatives><mixed-citation xml:lang="ru">Report to the President: Forensic Science in Criminal Courts: Ensuring Scientific Validity of Feature-Comparison Methods. CreateSpace Independent Publishing Platform, 2016. 132 p.</mixed-citation><mixed-citation xml:lang="en">Report to the President: Forensic Science in Criminal Courts: Ensuring Scientific Validity of Feature-Comparison Methods. CreateSpace Independent Publishing Platform, 2016. 132 p.</mixed-citation></citation-alternatives></ref><ref id="cit28"><label>28</label><citation-alternatives><mixed-citation xml:lang="ru">Li B., Li N. Handwriting Expertise Reliability: a Review // Journal of Forensic Science and Medicine. 2019. Vol. 5. No. 4. P. 181–186. https://doi.org/10.4103/jfsm.jfsm_44_19</mixed-citation><mixed-citation xml:lang="en">Li B., Li N. Handwriting Expertise Reliability: a Review. Journal of Forensic Science and Medicine. 2019. Vol. 5. No. 4. P. 181–186. https://doi.org/10.4103/jfsm.jfsm_44_19</mixed-citation></citation-alternatives></ref><ref id="cit29"><label>29</label><citation-alternatives><mixed-citation xml:lang="ru">Kang T.-Y., Kim H., Yook S., Lee J. A Study on Factors that Affect Error Rates in Handwriting Examinations of Korean Characters by Forensic Document Examiners and Non-Experts // Forensic Science International. 2022. Vol. 334. https://doi.org/10.1016/j.forsciint.2022.111266</mixed-citation><mixed-citation xml:lang="en">Kang T.-Y., Kim H., Yook S., Lee J. A Study on Factors that Affect Error Rates in Handwriting Examinations of Korean Characters by Forensic Document Examiners and Non-Experts. Forensic Science International. 2022. Vol. 334. https://doi.org/10.1016/j.forsciint.2022.111266</mixed-citation></citation-alternatives></ref><ref id="cit30"><label>30</label><citation-alternatives><mixed-citation xml:lang="ru">Crot S., Marquis R. A comparative Review of Error Rates in Forensic Handwriting Examination // Journal of Forensic Sciences. 2024. Vol. 69. No. 6. P. 2127–2138. https://doi.org/10.1111/1556-4029.15589</mixed-citation><mixed-citation xml:lang="en">Crot S., Marquis R. A comparative Review of Error Rates in Forensic Handwriting Examination. Journal of Forensic Sciences. 2024. Vol. 69. No. 6. P. 2127–2138. https://doi.org/10.1111/1556-4029.15589</mixed-citation></citation-alternatives></ref><ref id="cit31"><label>31</label><citation-alternatives><mixed-citation xml:lang="ru">Huber R.A. Handwriting Identification: Facts and Fundamentals. CRC Press, 1999. 456 p.</mixed-citation><mixed-citation xml:lang="en">Huber R.A. Handwriting Identification: Facts and Fundamentals. CRC Press, 1999. 456 p.</mixed-citation></citation-alternatives></ref><ref id="cit32"><label>32</label><citation-alternatives><mixed-citation xml:lang="ru">Fairhurst M.C. Signature Verification Revisited: Promoting Practical Exploitation of Biometric Technology // Electronics &amp; Communication Engineering Journal. 1997. Vol. 9. No. 6. P. 273–280.</mixed-citation><mixed-citation xml:lang="en">Fairhurst M.C. Signature Verification Revisited: Promoting Practical Exploitation of Biometric Technology. Electronics &amp; Communication Engineering Journal. 1997. Vol. 9. No. 6. P. 273– 280.</mixed-citation></citation-alternatives></ref><ref id="cit33"><label>33</label><citation-alternatives><mixed-citation xml:lang="ru">Kaur R., Rani R., Pahuja R. Text-Dependent and Text-Independent Writer Identification Approaches: Challenges and Future Directions // International Journal of Software Innovation. 2022. Vol. 10. No. 1. P. 1–23.</mixed-citation><mixed-citation xml:lang="en">Kaur R., Rani R., Pahuja R. Text-Dependent and Text-Independent Writer Identification Approaches: Challenges and Future Directions. International Journal of Software Innovation. 2022. Vol. 10. No. 1. P. 1–23.</mixed-citation></citation-alternatives></ref><ref id="cit34"><label>34</label><citation-alternatives><mixed-citation xml:lang="ru">Mitchell T.M. Machine Learning. McGraw-Hill, 1997. 414 p.</mixed-citation><mixed-citation xml:lang="en">Mitchell T.M. Machine Learning. McGraw-Hill, 1997. 414 p.</mixed-citation></citation-alternatives></ref><ref id="cit35"><label>35</label><citation-alternatives><mixed-citation xml:lang="ru">Zhang X.-Y., Xie G.S., Liu Ch.-L., Bengio Y. EndTo-End Online Writer Identification with Recurrent Neural Network // IEEE Transactions on Human-Machine Systems. 2016. Vol. 47. No. 2. P. 285–292. https://doi.org/10.1109/THMS.2016.2634921</mixed-citation><mixed-citation xml:lang="en">Zhang X.-Y., Xie G.S., Liu Ch.-L., Bengio Y. EndTo-End Online Writer Identification with Recurrent Neural Network. IEEE Transactions on Human-Machine Systems. 2016. Vol. 47. No. 2. P. 285–292. https://doi.org/10.1109/THMS.2016.2634921</mixed-citation></citation-alternatives></ref><ref id="cit36"><label>36</label><citation-alternatives><mixed-citation xml:lang="ru">Vaswani A., Shazeer N., Parmar N., Uszkoreit J., Jones L. et al. Attention is All You Need // Advances in Neural Information Processing Systems. 2017. Vol. 30.</mixed-citation><mixed-citation xml:lang="en">Vaswani A., Shazeer N., Parmar N., Uszkoreit J., Jones L. et al. Attention is All You Need. Advances in Neural Information Processing Systems. 2017. Vol. 30.</mixed-citation></citation-alternatives></ref><ref id="cit37"><label>37</label><citation-alternatives><mixed-citation xml:lang="ru">Tolosana R., Vera-Rodriguez R., Fierrez J., Ortega-Garcia J. Biometric Signature Verification Using Recurrent Neural Networks // 14th IAPR International Conference on Document Analysis and Recognition (ICDAR). IEEE, 2017. P. 652–657. https://doi.org/10.1109/icdar.2017.112</mixed-citation><mixed-citation xml:lang="en">Tolosana R., Vera-Rodriguez R., Fierrez J., Ortega-Garcia J. Biometric Signature Verification Using Recurrent Neural Networks. 14th IAPR International Conference on Document Analysis and Recognition (ICDAR). IEEE, 2017. P. 652–657. https://doi.org/10.1109/icdar.2017.112</mixed-citation></citation-alternatives></ref><ref id="cit38"><label>38</label><citation-alternatives><mixed-citation xml:lang="ru">Dhieb T., Njah S., Boubaker H., Ouarda W., Ayed M.B. et al. Towards a Novel Biometric System for Forensic Document Examination // Computers &amp; Security. 2020. Vol. 97. https://doi.org/10.1016/j.cose.2020.101973</mixed-citation><mixed-citation xml:lang="en">Dhieb T., Njah S., Boubaker H., Ouarda W., Ayed M.B. et al. Towards a Novel Biometric System for Forensic Document Examination. Computers &amp; Security. 2020. Vol. 97. https://doi.org/10.1016/j.cose.2020.101973</mixed-citation></citation-alternatives></ref><ref id="cit39"><label>39</label><citation-alternatives><mixed-citation xml:lang="ru">Yang W., Jin L., Liu M. DeepWriterID: An End-toEnd Online Text-Independent Writer Identification System // IEEE Intelligent Systems. 2016. Vol. 31. No. 2. P. 45–53. https://doi.org/10.1109/MIS.2016.22</mixed-citation><mixed-citation xml:lang="en">Yang W., Jin L., Liu M. DeepWriterID: An Endto-End Online Text-Independent Writer Identification System. IEEE Intelligent Systems. 2016. Vol. 31. No. 2. P. 45–53. https://doi.org/10.1109/MIS.2016.22</mixed-citation></citation-alternatives></ref><ref id="cit40"><label>40</label><citation-alternatives><mixed-citation xml:lang="ru">Chen Z., Yu H.-X., Wu A., Zheng W.-Sh. LetterLevel Online Writer Identification // International Journal of Computer Vision. 2021. Vol. 129. P. 1394–1409. https://doi.org/10.1007/s11263-020-01414-y</mixed-citation><mixed-citation xml:lang="en">Chen Z., Yu H.-X., Wu A., Zheng W.-Sh. LetterLevel Online Writer Identification // International Journal of Computer Vision. 2021. Vol. 129. P. 1394–1409. https://doi.org/10.1007/s11263-020-01414-y</mixed-citation></citation-alternatives></ref><ref id="cit41"><label>41</label><citation-alternatives><mixed-citation xml:lang="ru">Hameed M.M., Ahmad R., Kiah M.L.M., Murtaza G. Machine Learning-Based Offline Signature Verification Systems: A Systematic Review // Signal Processing: Image Communication. 2021. Vol. 93. https://doi.org/10.1016/j.image.2021.116139</mixed-citation><mixed-citation xml:lang="en">Hameed M.M., Ahmad R., Kiah M.L.M., Murtaza G. Machine Learning-Based Offline Signature Verification Systems: A Systematic Review // Signal Processing: Image Communication. 2021. Vol. 93. https://doi.org/10.1016/j.image.2021.116139</mixed-citation></citation-alternatives></ref><ref id="cit42"><label>42</label><citation-alternatives><mixed-citation xml:lang="ru">Khosroshahi S.N.M., Razavi S.N., Sangar A.B., Majidzadeh K. Deep Neural Networks-Based Offline Writer Identification Using Heterogeneous Handwriting Data: an Evaluation via a Novel Standard Dataset // Journal of Ambient Intelligence and Humanized Computing. 2022. Vol. 13. P. 2685–2704. https://doi.org/10.1007/s12652-021-03253-2</mixed-citation><mixed-citation xml:lang="en">Khosroshahi S.N.M., Razavi S.N., Sangar A.B., Majidzadeh K. Deep Neural Networks-Based Offline Writer Identification Using Heterogeneous Handwriting Data: an Evaluation via a Novel Standard Dataset. Journal of Ambient Intelligence and Humanized Computing. 2022. Vol. 13. P. 2685–2704. https://doi.org/10.1007/s12652-021-03253-2</mixed-citation></citation-alternatives></ref><ref id="cit43"><label>43</label><citation-alternatives><mixed-citation xml:lang="ru">Nguyen H.T., Nguyen C.T., Ino T., Indurkhya B., Nakagawa M. Text-Independent Writer Identification Using Convolutional Neural Network // Pattern Recognition Letters. 2019. Vol. 121. P. 104–112. https://doi.org/10.1016/j.patrec.2018.07.022</mixed-citation><mixed-citation xml:lang="en">Nguyen H.T., Nguyen C.T., Ino T., Indurkhya B., Nakagawa M. Text-Independent Writer Identification Using Convolutional Neural Network. Pattern Recognition Letters. 2019. Vol. 121. P. 104–112. https://doi.org/10.1016/j.patrec.2018.07.022</mixed-citation></citation-alternatives></ref><ref id="cit44"><label>44</label><citation-alternatives><mixed-citation xml:lang="ru">Chahi A., El merabet Y., Ruichek Y., Touahni R. WriterINet: a Multi-Path Deep CNN for Offline Text-Independent Writer Identification // International Journal on Document Analysis and Recognition (IJDAR). 2023. Vol. 26. P. 89–107. https://doi.org/10.1007/s10032-022-00418-3</mixed-citation><mixed-citation xml:lang="en">Chahi A., El merabet Y., Ruichek Y., Touahni R. WriterINet: a Multi-Path Deep CNN for Offline Text-Independent Writer Identification. International Journal on Document Analysis and Recognition (IJDAR). 2023. Vol. 26. P. 89–107. https://doi.org/10.1007/s10032-022-00418-3</mixed-citation></citation-alternatives></ref><ref id="cit45"><label>45</label><citation-alternatives><mixed-citation xml:lang="ru">Kumar P., Sharma A. Segmentation-free Writer Identification Based on Convolutional Neural Network // Computers &amp; Electrical Engineering. 2020. Vol. 85. https://doi.org/10.1016/j.compeleceng.2020.106707</mixed-citation><mixed-citation xml:lang="en">Kumar P., Sharma A. Segmentation-free Writer Identification Based on Convolutional Neural Network. Computers &amp; Electrical Engineering. 2020. Vol. 85. https://doi.org/10.1016/j.compeleceng.2020.106707</mixed-citation></citation-alternatives></ref><ref id="cit46"><label>46</label><citation-alternatives><mixed-citation xml:lang="ru">He Sh., Schomaker L. GR-RNN: Global-context Residual Recurrent Neural Networks for Writer Identification // Pattern Recognition. 2021. Vol. 117. https://doi.org/10.1016/j.patcog.2021.107975</mixed-citation><mixed-citation xml:lang="en">He Sh., Schomaker L. GR-RNN: Global-context Residual Recurrent Neural Networks for Writer Identification. Pattern Recognition. 2021. Vol. 117. https://doi.org/10.1016/j.patcog.2021.107975</mixed-citation></citation-alternatives></ref><ref id="cit47"><label>47</label><citation-alternatives><mixed-citation xml:lang="ru">Dey S., Dutta A., Toledo J.I., Ghosh S.K., Llados J. et al. SigNet: Convolutional Siamese Network for Writer Independent Offline Signature Verification // Pattern Recognition Letters. 2017. https://doi.org/10.48550/arXiv.1707.02131</mixed-citation><mixed-citation xml:lang="en">Dey S., Dutta A., Toledo J.I., Ghosh S.K., Llados J. et al. SigNet: Convolutional Siamese Network for Writer Independent Offline Signature Verification. Pattern Recognition Letters. 2017. https://doi.org/10.48550/arXiv.1707.02131</mixed-citation></citation-alternatives></ref><ref id="cit48"><label>48</label><citation-alternatives><mixed-citation xml:lang="ru">Kumar V., Sundaram S. Siamese Based Neural Network for Offline Writer Identification on Word Level Data // arXiv. 2022. https://doi.org/10.48550/arXiv.2211.14443</mixed-citation><mixed-citation xml:lang="en">Kumar V., Sundaram S. Siamese Based Neural Network for Offline Writer Identification on Word Level Data. arXiv. 2022. https://doi.org/10.48550/arXiv.2211.14443</mixed-citation></citation-alternatives></ref><ref id="cit49"><label>49</label><citation-alternatives><mixed-citation xml:lang="ru">Wang S., Jia S. Signature Handwriting Identification Based on Generative Adversarial Networks // Journal of Physics: Conference Series. 2019. Vol. 1187. No. 4. P. 42–47. https://doi.org/10.1088/1742-6596/1187/4/042047</mixed-citation><mixed-citation xml:lang="en">Wang S., Jia S. Signature Handwriting Identification Based on Generative Adversarial Networks. Journal of Physics: Conference Series. 2019. Vol. 1187. No. 4. P. 42–47. https://doi.org/10.1088/1742-6596/1187/4/042047</mixed-citation></citation-alternatives></ref><ref id="cit50"><label>50</label><citation-alternatives><mixed-citation xml:lang="ru">Kao H.-H., Wen Ch.-Y. An Offline Signature Verification and Forgery Detection Method Based on a Single Known Sample and an Explainable Deep Learning Approach // Applied Sciences. 2020. Vol. 10. No. 11. https://doi.org/10.3390/app10113716</mixed-citation><mixed-citation xml:lang="en">Kao H.-H., Wen Ch.-Y. An Offline Signature Verification and Forgery Detection Method Based on a Single Known Sample and an Explainable Deep Learning Approach. Applied Sciences. 2020. Vol. 10. No. 11. https://doi.org/10.3390/app10113716</mixed-citation></citation-alternatives></ref><ref id="cit51"><label>51</label><citation-alternatives><mixed-citation xml:lang="ru">Simonyan K., Vedaldi A., Zisserman A. Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps // arXiv. 2014. https://doi.org/10.48550/arXiv.1312.6034</mixed-citation><mixed-citation xml:lang="en">Simonyan K., Vedaldi A., Zisserman A. Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps. arXiv. 2014. https://doi.org/10.48550/arXiv.1312.6034</mixed-citation></citation-alternatives></ref><ref id="cit52"><label>52</label><citation-alternatives><mixed-citation xml:lang="ru">Marcinowski M. Top Interpretable Neural Network for Handwriting Identification // Journal of Forensic Sciences. 2022. Vol. 67. No. 3. P. 1140–1148. https://doi.org/10.1111/1556-4029.14978</mixed-citation><mixed-citation xml:lang="en">Marcinowski M. Top Interpretable Neural Network for Handwriting Identification. Journal of Forensic Sciences. 2022. Vol. 67. No. 3. P. 1140–1148. https://doi.org/10.1111/1556-4029.14978</mixed-citation></citation-alternatives></ref><ref id="cit53"><label>53</label><citation-alternatives><mixed-citation xml:lang="ru">Россинская Е.Р., Бодров Н.Ф. Современное состояние и перспективы исследования образов цифровых следов в судебной почерковедческой экспертизе // Криминалистика: вчера, сегодня, завтра. 2022. Т. 21. № 1. С. 121–135. https://doi.org/10.55001/2587-9820.2022.44.98.011</mixed-citation><mixed-citation xml:lang="en">Rossinskaya E.R., Bodrov N.F. The Current State and Prospects for the Study of Digital Trace Images in Forensic Handwriting Expertise. Forensics: Yesterday, Today, Tomorrow. 2022. Vol. 21. No. 1. P. 121–135 (In Russ.). https://doi.org/10.55001/2587-9820.2022.44.98.011</mixed-citation></citation-alternatives></ref><ref id="cit54"><label>54</label><citation-alternatives><mixed-citation xml:lang="ru">Журавель А.А., Трошко Н.В., Эджубов Л.Г. Использование алгоритма обобщенного портрета для опознавания образов в судебном почерковедении // Правовая кибернетика. 1970. С. 212–227.</mixed-citation><mixed-citation xml:lang="en">Zhuravel A.A., Troshko N.V., Edzhubov L.G. Using Generalized Portrait Algorithm for Pattern Recognition in Forensic Handwriting Examination. Legal Cybernetics. 1970. P. 212–227. (In Russ.).</mixed-citation></citation-alternatives></ref><ref id="cit55"><label>55</label><citation-alternatives><mixed-citation xml:lang="ru">Garrett B.L., Rudin C. Interpretable Algorithmic Forensics // Proceedings of the National Academy of Sciences. 2023. Vol. 120. No. 41. https://doi.org/10.1073/pnas.2301842120</mixed-citation><mixed-citation xml:lang="en">Garrett B.L., Rudin C. Interpretable Algorithmic Forensics. Proceedings of the National Academy of Sciences. 2023. Vol. 120. No. 41. https://doi.org/10.1073/pnas.2301842120</mixed-citation></citation-alternatives></ref><ref id="cit56"><label>56</label><citation-alternatives><mixed-citation xml:lang="ru">Хазиев Ш.Н., Штохов А.Н. Судебные экспертизы по делам об ошибочной биометрической идентификации // Теория и практика судебной экспертизы. 2024. Т. 19. № 3. С. 88–102. https://doi.org/10.30764/1819-2785-2024-3-88-102</mixed-citation><mixed-citation xml:lang="en">Khaziev Sh.N., Shtokhov A.N. Forensic Examination in Cases of Mistaken Biometric Identification. Theory and Practice of Forensic Science. 2024. Vol. 19. No. 3. P. 88–102. (In Russ.). https://doi.org/10.30764/1819-2785-2024-3-88-102</mixed-citation></citation-alternatives></ref><ref id="cit57"><label>57</label><citation-alternatives><mixed-citation xml:lang="ru">Хазиев Ш.Н. Криминалистические и судебно-экспертные основы современных биометрических технологий // Теория и практика судебной экспертизы. 2023. Т. 18. № 1. С. 16–21. https://doi.org/10.30764/1819-2785-2023-1-16-21</mixed-citation><mixed-citation xml:lang="en">Khaziev Sh.N. Forensic Basics of Modern Biometric Technologies. Theory and Practice of Forensic Science. 2023. Vol. 18. No 1. P. 16– 21. (In Russ.). https://doi.org/10.30764/1819-2785-2023-1-16-21</mixed-citation></citation-alternatives></ref></ref-list><fn-group><fn fn-type="conflict"><p>The authors declare that there are no conflicts of interest present.</p></fn></fn-group></back></article>
