Open Access
Issue
ITM Web Conf.
Volume 35, 2020
International Forum “IT-Technologies for Engineering Education: New Trends and Implementing Experience” (ITEE-2019)
Article Number 07005
Number of page(s) 12
Section Anthropological Dimension of Digital Technologies in Engineering Education
DOI https://doi.org/10.1051/itmconf/20203507005
Published online 09 December 2020
  1. Yu.I. Zhuravlev, On the algebraic approach to solving problems of recognition and classification, Problems of cybernetics 33, pp. 5-68 (1978) [Google Scholar]
  2. Alexander Alfimtsev, Sergey Sakulin, and Vladimir Devyatkov, Web personalization based on fuzzy aggregation and recognition of user activity, International Journal of Web Portals (IJWP) 4.1, pp. 33-41 (2012) [CrossRef] [Google Scholar]
  3. M.M. Bongard, The recognition problem, No. FTD-HT-23-194-68, FOREIGN TECHNOLOGY DIV WRIGHT-PATTERSON AFB OHIO (1968) [Google Scholar]
  4. I.B. Gurevich and Yu.I. Zhuravlev, Minimization of Boolean functions and effective recognition algorithms, Cybernetics 10.3, pp. 393-397 (1974) [Google Scholar]
  5. V.D. Mazurov and E.Yu. Polyakova, Committees: History and Applications in Machine Learning, International Conference on Mathematical Optimization Theory and Operations Research, Springer, Cham (2019) [Google Scholar]
  6. Yu.I. Zhuravlev, et al, Recognition and classification problems with standard training information, USSR Computational Mathematics and Mathematical Physics 20.5, pp. 195-211 (1980) [CrossRef] [Google Scholar]
  7. S.A. Aivazyan, Z.I. Bezhaeva and O.V. Staroverov, Classification of multidimensional observations, Statistika, Moscow, p. 238 (1974) [Google Scholar]
  8. E.M. Braverman and I.B. Muchnik, Structural methods of empirical data processing, Moscow, Nauka, GRAML (1983). [Google Scholar]
  9. V.N. Vapnik, Restoration of dependencies according to empirical data, Moscow, the science (1979) [Google Scholar]
  10. I.A. Deshin, et al, Development of software for the express diagnostics of skin pigmented lesions based on the analysis of clinical images, AIP Conference Proceedings, Vol. 2140, No. 1, AIP Publishing LLC (2019) [Google Scholar]
  11. N.I. Sidnyaev, Ju.I. Butenko and V.V. Garazha, Mathematical apparatus for engineering-linguistic models, AIP Conference Proceedings, Vol. 2195, No. 1, AIP Publishing LLC, (2019) [Google Scholar]
  12. A.L. Gorelik, V.A. Skrypkin, Methods of Recognition, Higher Education in Russia, 2nd edition, transcript and additional, Moscow: Vyshaya Shkola, p. 208 (1984) [Google Scholar]
  13. Patrick A. Edward and E. Earl, Swartzlander F undamentals of Pattern Recognition, IEEE Transactions on Systems, Man, and Cybernetics 5, pp. 528-528 (1973) [CrossRef] [Google Scholar]
  14. J. Tu and R. Gonzalez, Principles of pattern recognition, Moscow, “Mir” Publishers (World) (1978) [Google Scholar]
  15. J.T. Tou and R. C. Gonzalez, Pattern Recognition Principles Addison-Wesley, Reading, MA 377 (1974) [Google Scholar]
  16. Alfimtsev Alexander, Sergey Sakulin, and Vladimir Devyatkov, Web personalization based on fuzzy aggregation and recognition of user activity, International Journal of Web Portals (IJWP) 4.1, pp. 33-41 (2012) [CrossRef] [Google Scholar]
  17. Loktev Daniil, and Alexey Loktev, User Verification Based on the Analysis of His Images in the Distance Learning System, eLearning & Software for Education 3 (2019) [Google Scholar]
  18. Duda Richard O. and Peter E. Hart, Pattern recognition and scene analysis (1973). [Google Scholar]
  19. Fu King Sun, Syntactic methods in pattern recognition, Elsevier (1974) [Google Scholar]
  20. Egor Dmitriev, et al, Remote Sensing Methods for the Retrieval of Inventory and Bioproductivity Parameters of Forests Using High Resolution Satellite Images, E3S Web of Conferences, Vol. 75, EDP Sciences (2019) [Google Scholar]

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