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Oleg S. Seredin Ph.D., Associate
Professor Linkedin: oleg-seredin |
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Citizenship: The Russian Federation |
Machine
Learning, Data Mining, Pattern Recognition, Signal and Image Analysis, Visual
Representation of Multidimensional Data
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
M.S.
Degree in Engineering and Technologies for Automation and Control,
Tula State University, Department of
Cybernetics
Methods and Algorithms of Pattern Recognition Machine Learning on the Basis of Reliability Functions Estimation
B.S.
Degree in Engineering and Technologies for Automation and Control,
Tula State University, Department of Cybernetics
Visiting
Scientist,
National Taipei University of Technology,
Taipei, Taiwan
Visiting
Scientist,
Computing Center of the Russian Academy
of Sciences,
Moscow, Russia
Visiting
Scientist,
Markov Processes International, LLC,
New Jersey, USA
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)
Assistant
Professor,
Tula State
University, Department of Cybernetics
Teaching
Assistant,
Tula State
University, Department of Cybernetics
Ph.D.
Student,
Tula State
University, Department of Cybernetics
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.
Research
Assistant, then Researcher
Laboratory of Data Analysis
Tula State University, Department of Cybernetics (from 2014 Institute of
Applied Mathematics and Computer Science)
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
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
Personal Grant of the Albany-Tula
Alliance in 2009
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)
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)
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)
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)
Grant
of the Russian Foundation for Basic
Research:
“Detector combining in the signal and image
processing” (Tula State University, Principal Investigator Prof. O. Seredin)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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, 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
PhD Dissertation Supervision:
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
Dr. Khmelnitskiy
Denis, 2008, Tula State University
Dr. Genrikhov
Igor, 2013, Computing Center of Russian Academy of Science, Moscow
Dr. Domakhina
Ludmila, 2014, Moscow State University
Dr. Kusnetsov
Mikhail, 2016, Moscow Institute if Physics and Technology
Dr. Lomov
Nikita, 2020, Computing Center of Russian Academy of Science, Moscow
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 7th International Symposium on
Information and Communication Technology (SoICT
2016), Ho Chi Minh, Vietnam, December 2016
Member of Program Committee on the
9th, 11th, 12th IEEE International
Conference on Cloud Computing Technology and Science (CloudCom 2017, 2019,
2020)
Member of Program Committee on the 4th,
5th, 6th, 7th, 8th, 9th 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
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)
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”
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”
More than 80 publications, link to the Russian
Science Citation Index:
Profile
at Google Scholar Profile at
Scopus Author Profile at ResearchGate
Profile at ORCID Profile at Publons Profile at DBLP
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
S. Fedotova, O. Kushnir, and O. Seredin, 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 (VISIGRAPP 2020), 2020, vol. 4, pp. 398–404.
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.