1.    A. Makovetskii, V. Kober, “Analysis of the gradient descent method in problems of the signals and images restoration,” Pattern Recognition and Image Analysis, January 2015, Volume 25, Issue 1, P. 53-59, 2015. DOI: 10.1134/S1054661815010101 (Indexed in Scopus)
2.    Makovetskii A., Voronin S. and Kober V., “Explicit solutions of one-dimensional total variation problem,” Proc. SPIE's 60 Annual Meeting: Applications of Digital Image Processing XXXVIII, Vol. 9599, P. 959926-1, 2015. DOI: 10.1117/12.2187866 (Indexed in WoS, Scopus, Accession Number WOS: 000366385200063)
3.    С.М. Воронин, А.Ю. Маковецкий, В.И. Кобер, В.Н. Карнаухов, ”Свойства точных решений задачи регуляризации полной вариации функций одной переменной,” Информационные процессы, Том 15, No 2, стр. 162–168, 2015. (РИНЦ)
4.    Voronin S., Makovetskii A., Kober V. and Karnauhov V., ”Properties of exact solutions of the total variation regularization functions of one variable,” Journal of Communications Technology and Electronics, Vol. 60, No. 12, P. 1356–1359, 2015. DOI: 10.1134/S1064226915120207 (Indexed in WoS, Scopus. Impact Factor: 0.36, Accession Number: WOS: 000366638500011)
5.    A. Makovetskii, S. Voronin and V. Kober, ”Total variation regularization with bounded linear variations,” Proc. SPIE's 61 Annual Meeting: Applications of Digital Image Processing XXXIX, Vol. 9971, pp. 99712T-9, 2016. DOI: 10.1117/12.2237162(Indexed in WoS, Scopus. Accession Number WOS:000390023100086)
6.    Makovetskii A., Voronin S. and Kober V., “An efficient algorithm for total variation denoising,” Proc. Int. Conference of Analysis of Images, Social Networks, and Texts (AIST 2016), CCIS 661, pp. 326–337, 2017. DOI: 10.1007/978-3-319-52920-2_30 (Indexed in WoS, Scopus, Accession Number: WOS:000407059600030)
7.    Artyom Makovetskii, Sergei Voronin, Vitaly Kober, Dmitrii Tihonkih, “An efficient point-to-plane registration algorithm for affine transformations,” Proceedings SPIE Volume 10396, Applications of Digital Image Processing XL, 103962J, 2017. DOI: 10.1117/12.2273604 (Indexed in WoS, Scopus, Accession Number WOS: 000418443700071)
8.    Artyom Makovetskii, Sergei Voronin, Vitaly Kober, “A generalized Condat's algorithm of 1D total variation regularization,” Proceedings SPIE Volume 10396, Applications of Digital Image Processing XL, 103962K, 2017. DOI: 10.1117/12.2273618 ( Indexed in WoS, Scopus, Accession Number WOS: 000418443700072)
9.    Artyom Makovetskii, Sergei Voronin, Vitaly Kober, Dmitrii Tihonkih, “Affine registration of point clouds based on point-to-plane approach,”’ Procedia Engineering, Volume 201, Pages 322-330, 2017. DOI: 10.1016/j.proeng.2017.09.635 ( Indexed in WoS, Scopus, Accession Number WOS: 000426433500041)
10.    Artyom Makovetskii, Sergei Voronin, Vitaly Kober, “A fast one dimensional total variation regularization algorithm,” CEUR Workshop Proceedings Volume 1901, Pages 176-179, 2017. ISSN: 16130073. http://ceur-ws.org/Vol-1901/paper28.pdf(Indexed in Scopus)
11.    A. Makovetskii, S. Voronin, V. Kober, D. Tihonkih, “Affine registration of point clouds based on point-to-plane approach,” Cборник трудов III международной конференции «Информационные технологии и нанотехнологии» (ИТНТ-2017), 684-688, 2017. (РИНЦ)
12.    A. Makovetskii, S. Voronin, V. Kober, “A fast one dimensional total variation regularization algorithm,” Cборник трудов IIIмеждународной конференции «Информационные технологии и нанотехнологии» (ИТНТ-2017), 689-692, 2017. (РИНЦ)
13.    A. Makovetskii, S. Voronin, V. Kober, A. Voronin, “A non-iterative method for approximation of the exact solution to the point-to-plane variational problem for orthogonal transformations,” Mathematical Methods in the Applied Sciences, Volume41, n. 18, P. 9218-9230, 2018. DOI:10.1002/mma.5173 (Indexed in WoS, Scopus, Q2 WoS, Q1 Scopus, Impact factor: 1.18).
14.    A. Makovetskii, S. Voronin, V. Kober, A. Voronin, D. Tihonkih, “Point clouds registration based on the point-to-plane approach for orthogonal transformations,” CEUR Workshop Proceedings Volume 2210, Pages 236-242, 2018. ISSN: 1613-0073 http://ceur-ws.org/Vol-2210/paper31.pdf(Indexed in Scopus)
15.    A. Makovetskii, S. Voronin, V. Kober, A.Voronin, "A point-to-plane registration algorithm for orthogonal transformations," Proc. SPIE 10752, Applications of Digital Image Processing XLI, 107522R, 2018. DOI: 10.1117/12.2321396 (Indexed in WoS, Scopus, Accession Number WOS: 000450861700092)
16.    S. Voronin, V. Kober, A. Makovetskii, "Image dehazing usingtotal variation regularization," Proc. SPIE 10752, Applications of Digital Image Processing XLI, 107522T, 2018. DOI: 10.1117/12.2321636 (Indexed in WoS, Scopus, Accession Number WOS:000450861700094)
17.    A. Makovetskii, S. Voronin, V. Kober, "An efficient algorithm of3D total variation regularization," Proc. SPIE 10752, Applications of DigitalImage Processing XLI, 107522V,2018. DOI:10.1117/12.2321646(Indexed in WoS, Scopus, Accession Number WOS:000450861700096)
18.    A. Vokhmintsev,M. Timchenko, T. Botova, K. Mironov, A. Makovetskii, A.Kober, "Development of a method for constructing a 3D accurate map of thesurrounding environment ," Proc. SPIE 10752, Applications of Digital ImageProcessing XLI, 107521X,2018. DOI: 10.1117/12.2320194(Indexed in WoS, Scopus, Accession Number WOS:000450861700063)
19.    A. Vokhmintcev, A. Melnikov, M. Timchenko, A. Kozko, A. Makovetskii, A.Kober, "Development of methods for selecting features using deep learningtechniques based on autoencoders," Proc.SPIE 10752, Applications of DigitalImage Processing XLI, 1075227,2018. DOI: 10.1117/12.2320189(Indexed in WoS, Scopus, Accession Number WOS:000450861700073)
20.    A. Makovetskii, S. Voronin, V. Kober, “A fast total variation regularization algorithm for 2D piecewise constant radially symmetric functions,” Journal of Physics: Conference Series,Volume 1096, n. 1, 012041, 2018. DOI: 10.1088/1742-6596/1096/1/012041 (Indexed in Scopus)
21.    A. Makovetskii, S. Voronin, V. Kober, A. Voronin, D. Tihonkih, “Approximation of the exact solution of point clouds registration based on point-to-plane approach for orthogonal transformations,” Proc. ITNT-2018 (Сборник Трудов ИТНТ-2018, IV международная конференция и молодежная школа «Информационные технологии и нанотехнологии»), P.939-945, 2018. ISBN: 978-5-88940-146-9 (Indexed in RINC)
22.    A. Makovetskii, S. Voronin, V. Kober, “A fast total variation regularization algorithm for 2d piecewise constant radially symmetric functions,” Proc. ITNT-2018 (Сборник Трудов ИТНТ-2018, IV международная конференция и молодежная школа «Информационные технологии и нанотехнологии»), P. 930-938, 2018. ISBN: 978-5-88940-146-9 (Indexed in RINC)
23.    Dmitrii Tihonkih, Vitaly Kober, Artyom Makovetskii, Aleksei Voronin “An efficient 3D mapping framework,” Proc. SPIE 11137, Applications of Digital Image Processing XLII, 111372L,2019. DOI: 10.1117/12.2529632 (Indexed in WoS, Scopus)
24.    Sergei Voronin, Vitaly Kober, Artyom Makovetskii, Aleksei Voronin, “Image dehazing using spatially displaced images,” Proc. SPIE 11137, Applications of Digital Image Processing XLII, 111372M,2019. DOI: 10.1117/12.2529684 (Indexed in WoS, Scopus)
25.    Sergei Voronin, Vitaly Kober, Artyom Makovetskii, Aleksei Voronin, “Non-rigid ICP and 3D facial models,” Proc. SPIE 11137, Applications of Digital Image Processing XLII, 111372K,2019. DOI: 10.1117/12.2529525 (Indexed in WoS, Scopus)
26.    Artyom Makovetskii, Sergei Voronin, Vitaly Kober, Aleksei Voronin, “A Generalized Point-to-Point Approach for Orthogonal Transformations” CCIS, volume 1090,pp. 217-231,2019.DOI: 10.1007/978-3-030-33394-2_17 (Indexed in WoS, Scopus)
27.    Dmitrii Tihonkih, Artyom Makovetskii, Vitaly Kober, Aleksei Voronin, “Preliminary ICP stage for data-thinning based on object geometry,” Journal of Physics: Conference Series, Volume 1368, 032010,2019. DOI: 10.1088/1742-6596/1368/3/032010 (Indexed in Scopus)
28.    КоберВ.И., Маковецкий А.Ю., Воронин С.М., Карнаухов В.Н., “Быстрый алгоритм регуляризации полной вариации для класса радиально-симметричных функций,” Информационные процессы, Т. 19,No 1,С. 33-46,2019. (Indexed inRINC)
29.    V. I. Kober, ,A. Yu. Makovetskii, S. M. Voronin, and V. N. Karnaukhov, “A Fast Algorithm of Regularization of the Total Variation for the Class of Radially Symmetrical Functions,”Journal of Communications Technology and Electronics, Vol. 64, No. 12, pp. 1500–1507,2019.DOI: 10.1134/S1064226919120064(Indexed in WoS, Scopus,Q2 Scopus)

30.    J. Diaz-Escobar, V. Kober, V. Karnaukhov, M. Mozerov, “Recognition of breast abnormalities using phase features,” Journal of Communications Technology and Electronics, 2020, Vol. 65, No. 12, pp. 1476-1483. DOI: 10.1134/S1064226920120050.
31.    A. Ruchay, V. Kober,  K. Dorofeev, V. Kolpakov, S.  Miroshnikov, “Accurate body measurement of live cattle using three depth cameras and non-rigid 3D shape recovery,” Journal of Computers and Electronics in Agriculture, 2020, Vol. 179, 105821. DOI:  0.1016/j.compag.2020.105821. Indexed in WoS Q1, Scopus, РИНЦ. Impact Factor: 4.020.
32.    V. Kober, “Fast recursive computation of sliding DHT with arbitrary step,” Sensors, 2020, 20, 5556; DOI: 10.3390/s20195556. Indexed in WoS Q1, Scopus, РИНЦ. Impact Factor: 3.275.
33.    A. Makovetskii, S. Voronin, V. Kober, A. Voronin, “A regularized point cloud registration approach for orthogonal transformations,” Journal of Global Optimization, 2020, vol. 8, DOI: 10.1007/s10898-020-00934-8. Indexed in WoS Q1, Scopus, РИНЦ. Impact Factor: 1.805.
34.    A. Makovetskii, S. Voronin, V. Kober, A. Voronin, “Tube-based taut string algorithms for total variation regularization,” Mathematics, 2020, vol. 8, 1141; 20 pages, DOI: 10.3390/math8071141. Indexed in WoS Q1, Scopus, РИНЦ. Impact Factor: 1.747.
35.    V. Kober, “Recursive algorithms for computing sliding DCT with arbitrary step,” IEEE Sensors, 2020, 10. DOI: 10.1109/JSEN.2020.3023892. Indexed in WoS Q1, Scopus, РИНЦ. Impact Factor: 3.073.
36.    J. Diaz-Escobar, V. Kober, “Natural scene text detection and segmentation using phase-based regions and character retrieval,” Mathematical Problems in Engineering, 2020, Vol. 2020, Article ID 7067251, 17 pages. DOI: 10.1155/2020/7067251. Indexed in WoS, Scopus, РИНЦ. Impact Factor: 1.179.
37.    V. Kober, A. Ruchay, V. Karnaukhov, “Tracking multiple objects with locally adaptive generalized optimum correlation filters,” Journal of Communications Technology and Electronics, 2020, Vol. 65, No. 6, pp. 716-724. DOI: 10.1134/S1064226920060169. Indexed in WoS, Scopus, РИНЦ. Impact Factor: 0.51.
38.    A. Ortiz-González, V. Kober, V. Karnaukhov, M. Mozerov, “Algorithm for the design of a three-dimensional map of the environment with a depth camera,” Journal of Communications Technology and Electronics, 2020, Vol. 65, No. 6, pp. 690-697. DOI: 10.1134/S1064226920060224. Indexed in WoS, Scopus, РИНЦ. Impact Factor: 0.51.
39.    M. Ruiz-Rodriguez, V. Kober, V. Karnaukhov, M. Mozerov, “Algorithm for three-dimensional reconstruction of nonrigid objects,” Journal of Communications Technology and Electronics, 2020, Vol. 65, No. 6, pp. 698-705. DOI: 10.1134/S1064226920060248. Indexed in WoS, Scopus, РИНЦ. Impact Factor: 0.51.
40.    A. Makovetskii, S. Voronin, V. Kober, A. Voronin, “An efficient algorithm for non-rigid object registration,” Computer Optics, 2020, Vol. 44(1), pp. 67-73. DOI: 10.18287/2412-6179-CO-586. Indexed in WoS, Scopus Q1, РИНЦ. Impact Factor: 2.73.
41.    A. Ruchay, V. Kober, V. Karnaukhov, “Algorithm for estimating type and probability of impulse noise in color images,” Journal of Communications Technology and Electronics, 2019, Vol. 64, No. 12, pp. 1508–1512. DOI: 10.1134/S1064226919120143. Indexed in WoS, Scopus, РИНЦ. Impact Factor: 0.51.
42.    V. Kober, A. Makovetskii, S. Voronin, V. Karnaukhov, ”A fast algorithm of regularization of the total variation for the class of radially symmetrical functions,” Journal of Communications Technology and Electronics, 2019, Vol. 64, No. 12, pp. 1500–1507. DOI: 10.1134/S1064226919120064. Indexed in WoS, Scopus, РИНЦ. Impact Factor: 0.51.
43.    S. Voronin, V. Kober, A. Makovetskii, A. Voronin, “Image dehazing based on microscanning approach,” Proc. SPIE's Annual Meeting: Applications of Digital Image Processing XLIII, 2020, Vol. 11510, pp. 115102X-8. DOI: 10.1117/12.2568946. Indexed in WoS, Scopus, РИНЦ.
44.    A. Makovetskii, S. Voronin, V. Kober, A. Voronin,” An efficient algorithm of total variation regularization in the two-dimensional case,” Proc. SPIE's Annual Meeting: Applications of Digital Image Processing XLIII, 2020, Vol. 11510, pp. 115102Y-8. DOI: 10.1117/12.2568954. Indexed in WoS, Scopus, РИНЦ.
45.    A. Ruchay, K. Dorofeev, V. Kober, “Classification of breast abnormalities in digital mammography with a deep convolutional neural network,” Proc. SPIE's Annual Meeting: Applications of Digital Image Processing XLIII, 2020, Vol. 11510, pp. 115102D-8. DOI: 10.1117/12.2567252. Indexed in WoS, Scopus, РИНЦ.