Середин Олег Сергеевич

Scientific Interests:

Machine Learning, Data Mining, Pattern Recognition, Signal and Image Analysis, Visual Representation of Multidimensional Data

Academic History:

2001

Ph.D. Degree in Theoretical Foundations of Informatics,
Computing Center of the Russian Academy of Sciences, Moscow

Ph.D. Thesis:
Methods and Algorithms of Featureless Pattern Recognition
Supervisor Prof. V. Mottl

1998

M.S. Degree in Engineering and Technologies for Automation and Control,
Tula State University, Department of Cybernetics

M.S. Thesis:
Methods and Algorithms of Pattern Recognition Machine Learning on the Basis of Reliability Functions Estimation

1996

B.S. Degree in Engineering and Technologies for Automation and Control,
Tula State University, Department of Cybernetics

Scientific History:

2013 (February) and 2014 (February)

Visiting Scientist,
National Taipei University of Technology,
Taipei, Taiwan

2008 (July-December)

Visiting Scientist,
Computing Center of the Russian Academy of Sciences,
Moscow, Russia

2005 (May-August)

Visiting Scientist,
Markov Processes International, LLC,
New Jersey, USA

Since 2002

Associate Professor,
Tula State University, Department of Cybernetics (from 2014 Institute of Applied Mathematics and Computer Science)

Lecture Courses:
Informatics,
Fundamentals of Programming (PASCAL, C),
Object Oriented Programming (C++),
Machine Learning (also in English)

2001-2002

Assistant Professor,
Tula State University, Department of Cybernetics

1999-2001

Teaching Assistant,
Tula State University, Department of Cybernetics

1998-2001

Ph.D. Student,
Tula State University, Department of Cybernetics

1999 (June-September)

Visiting Scientist,
Department of Computer Science,
Rutgers, the State University of New Jersey, USA

Bioinformatics Initiative Project: Machine learning approach to protein fold class recognition when classes have low homology between their amino acid sequences.

1993 - Present

Research Assistant, then Researcher

Laboratory of Data Analysis
Tula State University, Department of Cybernetics (from 2014 Institute of Applied Mathematics and Computer Science)

Membership in Scientific Associations:

Member of the Russian Section of International Association of Pattern Recognition (IAPR)

Member of the INSTICC, Institute for Systems and Technologies of Information, Control and Communication

Awards:

Diploma of the Ministry of Higher Education of the Russian Federation for the best student research in 1997

Diploma of the Scientific Section of the VIII International Student Olympiad on Automatic Control for the Practical Contribution, Saint-Petersburg, Russia, 2000

Personal Grant of the President of the Russian Federation for Young Scientists Support, 2004-2005

Grant for Young Teachers of the Leading Russian State Universities of Vladimir Potanin Foundation in 2006-2007, 2008-2009 and 2009-2010

Personal Grant of the Albany-Tula Alliance in 2009

Participation in Scientific Grants:

2018-2020

Grant of the Russian Foundation for Basic Research:

“Methods and algorithms for constructing mathematically correct comparison functions of binary images based on skeletons” (Tula State University, Principal Investigator Prof. O. Seredin)

2019

Grant of the Tula State University:

“A Privacy Preserving Elderly Family Member Identification and Activity Recognition System in A Smart Home Using Deep Learning Models” (Tula State University, Principal Investigator Prof. O. Seredin)

2016-2018

Joint International Grant of the Russian Foundation for Basic Research and Ministry of Science and Technology, Taiwan:

“Emergency Event Detection and Recognition in Video Monitoring of Elderly Individuals for a Wireless Alert System” (Tula State University, National Taipei University of Technology, Principal Investigators Prof. O. Seredin and Prof. S-C. Huang)

2014-2015

Grant of the Fund of assistance to development of small forms of enterprises in scientific-technical sphere:

“Software for intellectual video analysis of microassembly layout objects and adaptive film resistors laser trimming” (CDALab, LLC, Principal Investigator, CEO, Prof. O. Seredin)

2014-2016

Grant of the Russian Foundation for Basic Research:

“Detector combining in the signal and image processing” (Tula State University, Principal Investigator Prof. O. Seredin)

2009-2011

Grant of the Russian Foundation for Basic Research:

“Methods of learning regularization in tasks of ordered and interrelated data analysis” (Tula State University, Principal Investigator Prof. O. Seredin)

2006-2008

Grant of the Russian Foundation for Basic Research:

“Methods and software for intelligent data analysis in public surveys” (Tula State University, Principal Investigator Prof. O. Seredin)

2005-2007

INTAS Research Project Nr: 04-77-7347:

“Principles of Dissimilarity-Based Pattern Recognition in Signals, Symbolic Sequences and Images” (CONSORTIUM: Czech Technical University in Prague, Faculty of Electrical Engineering – Czech Republic; Institute Scientific Council "Cybernetics" – Russia; Tula State University – Russia; International Research and Training Centre for Information Technologies and Systems – Ukraine; University of Surrey - United Kingdom; Technische Universitat Dresden – Germany)

2004-2005

Personal Grant of the President of the Russian Federation for Young Scientists Support:

“Developing of New Algorithms for Signals and Images Featureless Recognition Based on Mutual Alignment and Potential Functions Method” (Tula State University, Principal Investigator Prof. O. Seredin)

2004-2005

Grant of the Russian Foundation for Basic Research:

“Methods and Software of Pattern Recognition in Spatial Data Sets of Seismic Explorations for Prospecting Oil and Gas Collectors in Massive Rocks with Respect to Train Information from Sparse Net of Wells” (Tula State University, Principal Investigator Prof. A. Kopylov)

2002-2004

Grant of the Russian Foundation for Basic Research:

“Methods and Algorithms of Pattern Recognition in Absence of A Priory Known Feature Vectors of Objects” (Computing Centre of Russian Academy of Science, Principal Investigator Prof. V. Mottl)

2002

Grant of the Russian Foundation for Basic Research:

“Mathematically Consistent Similarity Measures for Elements of Biological Sequences in Bioinformatics Researches” (Tula State University, Principal Investigator Prof. O. Seredin)

1998-2000

Grant of the Ministry of Higher Education of the Russian Federation:

“Hidden Markov Models for Typical Problems of Signal and Image Analysis” (Tula State University, Principal Investigator Prof. V. Mottl)

1999-2001

Grant of the Federal Program of the Russian Federation “Perspective Information Technologies”:

“Variational Methods for the Analysis of Images, Signals and Symbolic Sequences”

(Tula State University, Principal Investigator Prof. V. Mottl)

1999-2001

Grant of the Russian Foundation for Basic Research:

“Unified Machine Learning Framework for Signal and Image Analysis on the Basis of the Variational Approach”

(Tula State University, Principal Investigator Prof. V. Mottl)

Actual Participation in Scientific Conferences:

3-d, 5-th, 6-th, 7-th, 8-th and 9th Conferences on Pattern Recognition and Image Analysis
(Nizhni Novgorod, Russia, 1997, 2008; Samara, Russia, 2000; Velikiy Novgorod, Russia, 2002; St. Petersburg, Russia, 2004, Yoshkar-Ola, Russia, 2007)

9-th, 10-th, 11-th, 13-th, 14-th, 15-th,16-th, 17-th and 18-th Conferences on Mathematical Methods in Pattern Recognition
(Tver, Russia, 1999; Zvenigorod, Russia, 2001; Pushchino, Russia, 2003; Zelenogorsk, Russia, 2007; Suzdal, Russia, 2009; Petrozavodsk, Russia, 2011; Kazan, Russia, 2013; Svetlogorsk, Russia, 2015; Taganrog, Russia, 2017; Moscow, Russia, 2019)

International Conference on Machine Learning and Data Mining (MLDM) in Pattern Recognition
(Leipzig, Germany, 2001, 2009)

International Conference on Pattern Recognition and Information Processing (PRIP)
(Minsk, Belarus, 2007)

7-th, 8-th, 9-th, 10-th, 11-th and 13-th  International Conferences on Intelligent Information Processing
(Alushta, Ukraine, 2008; Paphos, Cyprus, 2010; Budva, Montenegro, 2012; Crete, Greece, 2014; Barcelona, Spain, 2016, Moscow, Russia, online, 2020)

6-th International Conference on Image and Signal Processing 2014 (ICISP 2014)
(Cherbourg, Normandy, France, 2014)

7-th International Symposium on Information and Communication Technology (SoICT 2016), Ho Chi Minh, Vietnam, 2016

ISPRS International Workshop (PSBB), Moscow, Russia, 2017, 2019

Technical Vision in Control Systems (TVCS), Moscow, Russia, 2012-2015, 2017, 2018

The 4-th International Professors Day on ICT Algorithm Design (ICTAD-2017), Moscow, Russia, 2017

RFBR-MOST Scientific Anniversary Conference, Taipei, Taiwan, 2018

The 7-th International Conference, ICPRAM 2018, Funchal, Madeira, Portugal, January 16-18, 2018

Huawei Augmented Reality, SLAM, 3D sensing Workshop, Kaliningrad, Russia, November 28-29, 2019

International workshop on Recent Advances in Machine Learning, Data Science, Intelligent Systems & Networking, (MaDaIN-2020), December 5, 2020, online

25-th International Conference on Pattern Recognition, January 2020, online

Academic Supervision Activity

PhD Dissertation Supervision:

E. Ryzhkov, PVS-Studio, CEO

PhD Thesis, Tula State University, Russia, 2009. Title: “Static code analysis for automated error detection while porting programs to 64-bit platforms"

O. Kushnir, Tula State University, Assistant Professor

PhD Thesis, Tula State University, Russia, 2018. Title: “Methods and algorithms for comparing shapes of binary raster images based on skeletonization"

Short-term Visiting Young Scientist Supervision:

Bo-Hao Chen from National Taipei University of Technology, 2014

“Development of algorithms for improving the quality of images obtained in bad weather conditions for improved computer vision systems” (Supervision jointly with prof. A. Kopylov)

A. Larin from Moscow Institute of Physics and Technology, 2014

“Methods and algorithms for one-class classification with outliers in the training set”

Master Students Supervision:

More than 20 Master of Science students at Tula State University

Official Opponent for PhD Dissertation Defense:

Dr. Khmelnitskiy Denis, 2008, Tula State University

Dr. Genrikhov Igor, 2013, Computing Center of the Russian Academy of Science, Moscow

Dr. Domakhina Ludmila, 2014, Moscow State University

Dr. Kusnetsov Mikhail, 2016, Moscow Institute of Physics and Technology

Dr. Lomov Nikita, 2020, Computing Center of the Russian Academy of Science, Moscow

Reviewer for Conferences and Journals, Conferences Section Chair, Member of Program Committee:

Reviewer of the SN Computer Science Journal

Reviewer of the IEEE Signal Processing Letters

Reviewer of the Journal of Machine Learning and Data Analysis

Reviewer of the Journal of Computer Optics

Reviewer of the Sensors - Open Access Journal

Reviewer of the Applied Sciences - Open Access Journal

Section chair on the 7^th International Symposium on Information and Communication Technology (SoICT 2016), Ho Chi Minh, Vietnam, December 2016

Member of Program Committee on the 9th, 11^th, 12^th IEEE International Conference on Cloud Computing Technology and Science (CloudCom 2017, 2019, 2020)

Member of Program Committee on the 4^th, 5^th, 6^th, 7^th, 8^th, 9^th International Conference on Analysis of Images, Social Networks, and Texts (AIST-2015, AIST-2016, AIST-2017, AIST-2018, AIST-2019, AIST-2020)

Member of Program Committee on the ISPRS International Workshop – PSBB-2017, 2019, 2021

Member of Program Committee on the 27th and 28th International Conference on Computer Graphics and Vision ‑ GraphiCon 2017, 2019

Member of Program Committee on the International Conference on Pattern Recognition in Bioinformatics 2014 (PRIB-2014)

Member of Program Committee on International Conference on Computer Vision Theory and Applications 2018, 2019, 2020, 2021 (VISAPP-2018, 2019, 2020, 2021)

Member of Program Committee on International workshop on Recent Advances in Machine Learning, Data Science, Intelligent Systems & Networking 2020 (MaDaIN-2020)

Participation in Industry Projects:

AutomatedQA (SmartBear) LLC, 2007-2008, Project “OCR System for Computer Interface Screenshots”

SpecStroyAliance LLC, 2011, Project “Fire Detection Alarm System”

Mertsalov Sole Proprietorship, 2013-2016, Project “Building a Highly Efficient Software System for Text Data Mining”

Lasers&Apparatus LLC, 2014-2015, Project “Intellectual Video Analysis of Microassembly Layout Objects and Adaptive Film Resistors Laser Trimming”

IToolabs LLC, 2017-2019, Project “Emotion Recognition in Phone Calls”

Huawei Moscow Research Center, 2019, Project “Depth Map Resolution Upscaling based on Sparse Data from the Depth Sensor”

Publications in Russian:

More than 80 publications in Russian, link to the Russian Science Citation Index:

 

Publications in English:

 

Profile at Google Scholar   Profile at Scopus Author   Profile at ResearchGate   Profile at ORCID   Profile at Publons   Profile at DBLP

 

 Larin A. O., Seredin O. S., Kopylov A. V. One-Class Classification Criterion Robust to Anomalies in Training Dataset //Pattern Recognition. ICPR International Workshops and Challenges: Virtual Event, January 10–15, 2021, Proceedings, Part V. – Springer International Publishing, 2021. – pp. 155-165. DOI https://doi.org/10.1007/978-3-030-68821-9_15

 Aleksandr O. Larin, Oleg Seredin, and Andrei Kopylov. 2020. Reducing the Impact of Outliers on the One-Class Classification Decision Rule. In The 4th International Conference on Future Networks and Distributed Systems (ICFNDS) (ICFNDS '20). Association for Computing Machinery, New York, NY, USA, Article 55, 1–5. DOI:https://doi.org/10.1145/3440749.3442662

 Seredin O.S., Kopylov A.V. Surkov E.E. The study of skeleton description reduction in the human fall-detection task. Computer Optics 2020; 44(6): 951-958. DOI: 10.18287/2412-6179-CO-753.

 V. Vakurin, A. Kopylov, K. Mertsalov, and O. Seredin, “A multiclass words classification by the recurrent neural network with memory (LSTM) as applicable to the named entity recognition problem,” in CEUR Workshop Proceedings, 2020, vol. 2667, pp. 293–298.

 Kopylov, A., Seredin, O., Filin, A. et al. Detection of interactive voice response (IVR) in phone call records. Int J Speech Technol, 23, pp. 907-915 (2020). https://doi.org/10.1007/s10772-020-09754-3

 Fedotova, S.; Kushnir, O. and Seredin, O. (2020). Comparison of Binary Images based on Jaccard Measure using Symmetry Information.  In Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, ISBN 978-989-758-402-2, ISSN 2184-4321, pages 398-404.  DOI: 10.5220/0008989803980404 

 Sulimova V., Seredin O., Mottl V. Recognition of Herpes Viruses on the Basis of a New Metric for Protein Sequences //Journal of Physics: Conference Series. – IOP Publishing, 2019. – Vol. 1368. – No. 5. – p. 052039. doi:10.1088/1742-6596/1368/5/052039

 Kushnir O. A., Seredin O. S., Fedotova S. A. Algorithms for Adjustment of Symmetry Axis Found for 2d Shapes by the Skeleton Comparison Method //International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. – 2019. – Vol. 42. – No. 2/W12, pp. 129-136. DOI: 10.5194/isprs-archives-XLII-2-W12-129-2019

 Seredin O. S., Kopylov, A. V., Huang, S. C., & Rodionov, D. S. A Skeleton Features-Based Fall Detection Using Microsoft Kinect v2 with One Class-Classifier Outlier Removal //International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. – 2019. – Vol. 42. – No. 2/W12, pp.189-195. DOI: 10.5194/isprs-archives-XLII-2-W12-189-2019

 Gochoo, M., Tan, T. H., Batjargal, T., Seredin, O., & Huang, S. C. Device-Free Non-Privacy Invasive Indoor Human Posture Recognition Using Low-Resolution Infrared Sensor-Based Wireless Sensor Networks and DCNN. In 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2018, October, pp. 2311-2316.

 Shi, L. F., Chen, B. H., Huang, S. C., Larin, A., Seredin, O., Kopylov, A., & Kuo, S. Y. (2018). Removing Haze Particles from Single Image via Exponential Inference with Support Vector Data Description. IEEE Transactions on Multimedia, vol. 20, no. 9, pp. 2503-2512, Sept. 2018.

 Mottl V., Seredin O., Krasotkina O. Compactness hypothesis, potential functions, and rectifying linear space in machine learning //Braverman Readings in Machine Learning. Key Ideas from Inception to Current State. – Springer, Cham, 2018. – pp. 52-102.

 Kopylov, A., Seredin, O., Kushnir, O., Gracheva, I. and Larin, A. Background-Invariant Robust Hand Detection based on Probabilistic One-Class Color Segmentation and Skeleton Matching // Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2018). P. 503-510. ISBN: 978-989-758-276-9

 S. Fedotova, O. Seredin, and O. Kushnir. The Parallel Implementation of Algorithms for Finding the Reflection Symmetry of the Binary Images // Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W4, 179-184. http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W4/179/2017/. doi:10.5194/isprs-archives-XLII-2-W4-179-2017, 2017

 Kushnir O., Fedotova S., Seredin O., Karkishchenko A. Reflection Symmetry of Shapes Based on Skeleton Primitive Chains // Fifth International Conference, AIST 2016, Yekaterinburg, Russia, April 7–9, 2016, Revised Selected Papers, CCIS, Vol. 661, pp. 293–304, Springer International Publishing Switzerland (2016).

 Chen, B. H., Kopylov, A., Huang, S. C., Seredin, O., Karpov, R., Kuo, S. Y., ... & Gong, C. S. (2016). Improved global motion estimation via motion vector clustering for video stabilization. Engineering Applications of Artificial Intelligence, 54, 39-48.

 Kushnir O., Seredin O. Shape Matching Based on Skeletonization and Alignment of Primitive Chains. // M.Yu. Khachay, N. Konstantinova, A. Panchenko, D.I. Ignatov, G.V. Labunets (Eds.): Analysis of Images, Social Networks and Texts. Fourth International Conference, AIST 2015, Yekaterinburg, Russia, April 9-11, 2015, Revised Selected Papers. Communications in Computer and Information Science, Vol. 542, Springer, pp. 123–136 (2015)

 Krasotkina O., Seredin O., Mottl V. Supervised Selective Combination of Diverse Object-Representation Modalities for Regression Estimation //Multiple Classifier Systems. – Springer International Publishing, 2015. – pp. 89-99.

 A. Gubareva, V. Sulimova, O. Seredin, A. Larin, V. Mottl. Finding the largest hypercavity in a linear data space. Proceedings of the 22nd International Conference on Pattern Recognition, Stockholm, Sweden, August 24-28, 2014, pp. 4406-4410.

 Larin, A., Seredin, O., Kopylov, A., Kuo, S. Y., Huang, S. C., & Chen, B. H.  Parametric Representation of Objects in Color Space Using One-Class Classifiers //Machine Learning and Data Mining in Pattern Recognition. – Springer International Publishing, 2014. – pp. 300-314.

 Kushnir O., Seredin O. Parametric Description of Skeleton Radial Function by Legendre Polynomials for Binary Images Comparison // A. Elmoataz et al. (Eds.): ICISP 2014, LNCS 8509, pp. 520–530. Springer International Publishing Switzerland (2014)

 Fan-Chieh Cheng, Bo-Hao Chen, Shih-Chia Huang, Kuo, S.-Y., Vishnyakov, B., Kopylov, A., Vizilter, Y., Mestetskiy, L., Seredin, O., Vygolov, O. An automatic motion detection algorithm for transport monitoring systems //Consumer Electronics (ISCE), 2013 IEEE 17th International Symposium on. – IEEE, 2013. – С. 195-196.

 Oleg Seredin, Vadim Mottl, Alexander Tatarchuk, Nikolay Razin, David Windridge, Convex Support and Relevance Vector Machines for Selective Multimodal Pattern Recognition //21st International Conference on Pattern Recognition (ICPR 2012) November 11-15, 2012. Tsukuba, Japan, pp.1647-1650.

 Nikolay Razin, Dmitry Sungurov, Vadim Mottl, Ivan Torshin, Valentina Sulimova, Oleg Seredin, David Windridge: Application of the Multi-modal Relevance Vector Machine to the Problem of Protein Secondary Structure Prediction. PRIB 2012: 153-165.

 Degtyarev N., Seredin O. "A Geometric Approach to Face Detector Combining ", C. Sansone, J. Kittler, and F. Roli (Eds.): MCS 2011, LNCS 6713, pp. 299–308, Springer-Verlag Berlin Heidelberg (2011).

 Degtyarev N., Seredin O.: Comparative Testing of Face Detection Algorithms:In A. Elmoataz et al. (Eds.): ICISP 2010, LNCS 6134, pp. 200-209, Springer, Heidelberg (2010).

 O. Seredin, A. Kopylov, V. Mottl, Selection of Subsets of Ordered Features in Machine Learning // Transactions on Machine Learning and Data Mining, Vol. 2, No. 2, 2009, pp. 65-79.

 O. Seredin, A. Kopylov, V. Mottl, A. Pryimak, Selection of subsets of interrelated features in pattern recognition problem // In: Proceedings of 9th International Conference “Pattern Recognition and Image Analysis: New Information Technologies”, Nizhni Novgorod, 2008, Vol. 2, pp. 151-154.

Seredin O.S., Krestinin I.A. Face detection using peculiar point technique, In: Proceedings of 8th International Conference “Pattern Recognition and Image analysis: New Information Technologies”, Vol.2 –Yoshkar-Ola, 2007, pp. 335–338.

Mottl V., Tatarchuk A., Sulimova V., Krasotkina O., and Seredin O. Combining Pattern Recognition Modalities at the Sensor Level Via Kernel Fusion, In: Proceedings of 7th International Workshop Multiple Classifiers Systems, Prague, Czech Republic, 2007, pp. 1–12.

 Seredin O., Mottl V. Regularization in Image Recognition: the Principle of Decision Rule Smoothing In: Proceedings of the Ninth International Conference Pattern Recognition and Information Processing, Minsk, Belarus, 2007. Vol.II., pp. 151-155.

Mottl V.V., Seredin O.S., Krasotkina O.V., and Muchnik I.B. Fusing of potential functions in reconstructing dependences from empirical data In: Doklady Mathematics, Vol. 71, No. 2, 2005, pp. 315–319. From Doklady Akademii Nauk, Vol. 401, No. 5, 2005, pp. 607–612.

Mottl V.V., Seredin O.S., Krasotkina O.V., and Muchnik I.B. Principles of multi-kernel data mining. In: P. Perner and A. Imiya (Eds.), Machine Learning and Data Mining in Pattern Recognition, Springer Verlag, LNAI  3587, 2005, pp. 52 – 61.

Mottl V.V., Seredin O.S., Krasotkina O.V., and Muchnik I.B. Kernel fusion and feature selection in machine learning. Proceedings of the eighth IASTED International Conference Intelligent Systems and Control, October 31 – November 2, 2005, Cambridge, USA, pp.477-482.

Mottl V.V., Seredin O.S., Krasotkina O.V., Muchnik I.B. Fusion of Euclidian metrics in featureless data analysis: an equivalent of the classical problem of feature selection In: Proceedings of 7th International Conference on Pattern Recognition and Image Analysis, PRIA-7-2004, St. Petersburg, October, 2004, pp.94-97.

Mottl V.V., Seredin O.S., Sulimova V.V. Mathematically correct methods of similarity measurement on sets of signals and symbol sequences of different length. Proceedings of 7th International Conference on Pattern Recognition and Image Analysis, PRIA-7-2004, St. Petersburg, October, 2004, pp.98-101.

Seredin O.S. Experimental Study of A Priori Preferences for Decision Rules in Hilbert Spaces of Recognition Objects. Pattern Recognition and Image Analysis. Advances in Mathematical Theory and Applications, 2003, Vol. 13, No. 1, pp. 55–58.

Skorkin A.V., Seredin O.S. Algorithm for Selecting Template Objects for a Nonparametric Classifier. Pattern Recognition and Image Analysis. Advances in Mathematical Theory and Applications, 2003, Vol. 13, No. 2, pp. 345–348.

Mottl V.V., Seredin O.S., Dvoenko S.D., Kulikowski C.A, Muchnik I.B. Featureless pattern recognition in an imaginary Hilbert space. In: Proceedings of 16th International Conference Pattern Recognition, ICPR-2002, Quebec City, Canada, August, 2002, vol.II, pp.88-91.

Mottl V.V., Kostin A.A., Seredin O.S., Yermakov A.S., Kittler J. Support object classifiers with rigid and elastic kernel functions for face identification. In: Proceedings of 16th International Conference Pattern Recognition, ICPR-2002, Quebec City, Canada, August, 2002, vol.IV, pp.205-208.