1. Nesterov G. A., Shestakova A. O., Karyakin Yu. E. Automation of verification of scientific and technical documentation. Mathematical and Information Modeling. Proc. All-Russian Conf. of Young Scientists. Tyumen, University of Tyumen; 2021;19:97-101. (In Russian.) EDN: IAINCM.
2. Zobnina V. E., Vikhor N. A. Automation of checking the formatting of a text document. Selected Reports of the 65th Anniversary University Scientific and Technical Conf. of Students and Young Scientists. Collection of Reports. Tomsk, Tomsk State University of Architecture and Building; 2019:880-881. (In Russian.) EDN: WOXVEH.
3. Pozdin V. N., Vyimova E. A. Algorithm for automated standard control of the work of students of an educational institution. Society. Science. Innovations (Scientific and Practical Conference-2021). Collection of articles 21th AllRussian Scientific and Practical Conf. Kirov, Vyatka State University; 2021;2:584-588. (In Russian.) EDN: HMPOFQ.
4. Starichenko B. E., Ustinov M. A. Program of automation verification of text documents formatting. Pedagogical Education in Russia. 2018;(8):163-168. (In Russian.) EDN: UYIHPU. https://doi.org/10.26170/po18-08-22.
5. Karmanova K. A., Kudryavtseva A. G., Rybnikova V. V. Research and creation of a service for checking the design and formatting of documents. Proc. Scientific and Technical Conf. of Students, Postgraduate Students and Young Specialists named after E. V. Armensky. Moscow, HSE Tikhonov Moscow Institute of Electronics and Mathematics; 2022:113-116. (In Russian.) EDN: ZBXIVU. Available at: https://miem.hse.ru/data/2022/09/02/1700621959/MIEM-HSE-2022-final.pdf
6. ZhigalovaM., Sukhov A. System of automated checking of textual document design rules. Information Content and Processing. 2015;2(2):164-180. Available at: http://www.foibg.com/ijicp/vol02/ijicp02-02-p05.pdf
7. Martsinkevich V. I., Larionova G. S., Tereshchenko V. V., Sitnikova K. A., Gorlushkina N. N. Analysis of the possibilities of parsing electronic text documents for the automation of standard control. Economics. Law. Innovation. 2022;(3):39- 49. (In Russian.) EDN: JLQANQ. https://doi.org/10.17586/2713-1874-2022-3-47-57.
8. Kobets E. A., Nasyrov N. F., Komarov M. S., Gorlushkina N. N. The algorithm of formalization the requirements for the execution of documents for the automation norm rule checking service. Sovremennaya Nauka: Aktual’nyye Problemy Teorii i Praktiki. Seriya: Yestestvennyye i Tekhnicheskiye Nauki. 2021;(7):89-95. (In Russian.) EDN: INOAIN. https://doi.org/10.37882/2223-2966.2021.07.20.
9. Kobets E. A., Nasyrov N. F., Tartynskikh P. S., Gorlushkina N. N. Creation the object model of the text benchmark document for automation the norm rule checking service. Sovremennaya Nauka: Aktual’nyye Problemy Teorii i Praktiki. Seriya: Yestestvennyye i Tekhnicheskiye Nauki. 2021;(8):57-63. (In Russian.) EDN: BVPPMU. https://doi.org/10.37882/2223-2966.2021.08.14.
10. Kozyreva A., Nazarenko U., Berezhkov A., Nasyrov N. Analysis of the text of the FQP for automated standard control of documents. Journal of Physics: Conference Series. 2021;2131(2):1-7. https://doi.org/10.1088/1742-6596/2131/2/022102.
11. Martsinkevich V., Tereshchenko V., Larionova G., Berezhkov A., Kobets E., Nasyrov N., Gorlushkina N. Web tool for automated document formatting verification. Proc. 33rd Conf. of FRUCT Association. Helsinki, Finland, FRUCT Oy; 2023;(2):375-381. Available at: https://fruct.org/publications/volume-33/acm33/files/Mar.pdf
12. Zakharova A. A., Averyanova A. M., Glukhikh K. D. Automated information system for normative control at a university: Modeling of management processes. Innovative Technologies in Mechanical Engineering. Proc. of the 14th Int. Scientific and Practical Conf. Tomsk, National Research Tomsk Polytechnic University; 2023:149-152. (In Russian.) EDN: XOZDBC. Available at: https://earchive.tpu.ru/handle/11683/76559
13. Zakharova A. A., Averjyanova A.M., Glukhikh K. D. Web application for automating process of conducting standard control of educational documentation. Modern Education: Integration of Education, Science, Business and Government. Transformation of Education, Science and Manufacturing - the Basis of a Technological Breakthrough. Proc. Int. Scientific and Methodological Conf. Tomsk, Tomsk State University of Control Systems and Radioelectronics; 2023:260-263. (In Russian.) EDN: XLTURO.
14. Slivin A. N., Shakura V. A. Information system for automated control of final qualification papers design. Measurements, Automation and Modeling in Industry and Scientific Research (MAMI-2022). Proc. 17th All-Russian Scientific and Technical Conf. of Students, Postgraduate Students and Young Scientists with International Participation. Biysk, Polzunov Altai State Technical University; 2022:11-12. (In Russian.) EDN: JVHVXU.
15. Pfitzmann B., AuerC., DolfiM., Nassar A.S., Staar P. DocLayNet: A large human-annotated dataset for documentlayout segmentation. Proc. 28th ACM SIGKDD Conf. on Knowledge Discovery and Data Mining. New York, NY, USA, Association for Computing Machinery; 2022:3743-3751. https://doi.org/10.1145/3534678.3539043.
16. Bhowmik S., Kundu S., Sarkar R. BINYAS: A complex document layout analysis system. Multimedia Tools and Applications. 2021;80(6):8471-8504. https://doi.org/10.1007/s11042-020-09832-3.
17. Grijalva F., Santos E., Acuña B., Rodríguez J. C., Larco J. C. Deep learning in time-frequency domain for document layout analysis. IEEE Access. 2021;9:151254-151265. https://doi.org/10.1109/ACCESS.2021.3125913.
18. Wu X., Ma T., Du X., Hu Z., Yang J., He L. DRFN: A unified framework for complex document layout analysis. Information Processing & Management. 2023;60(3):1-16. https://doi.org/10.1016/j.ipm.2023.103339.
19. Wang B., ZhouJ., Zhang B. MSNet: A multi-scale segmentation network for documents layout analysis. Learning Technologies and Systems. Proc. 19th Int. Conf. on Web-Based Learning (ICWL 2020) and 5th Int. Symposium on Emerging Technologies for Education (SETE 2020). Springer-Verlag, Berlin, Heidelberg; 2021:225-235. https://doi.org/10.1007/978-3-030-66906-5_21.
20. Zhang P., Li C., Qiao L., Cheng Z., Pu S., Niu Y., Wu F. VSR: A unified framework for document layout analysis combining vision, semantics and relations. Document Analysis and Recognition. Proc. 16th Int. Conf. (ICDAR 2021). Berlin, Heidelberg, Germany, Springer-Verlag; 2021;1:115-130. https://doi.org/10.1007/978-3-030-86549-8_8.