"Markov Models for Pattern Recognition: From Theory to Applications"

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Book	Author(s)	Year	Publisher
Markov Models for Pattern Recognition: From Theory to Applications	Gernot A. Fink	2nd ed. 2014	Springer London
Markov Models for Pattern Recognition: From Theory to Applications	Gernot A. Fink	2008	Springer Berlin Heidelberg
Markov models for pattern recognition: From theory to applications	Fink G.A.	2008	Springer
Markov Models for Handwriting Recognition	Thomas Plötz; Gernot A. Fink	2011	Springer London
Pattern Recognition Theory and Applications	Pierre A. Devijver; Josef Kittler	1987	Springer Berlin Heidelberg
Pattern recognition theory and applications	NATO Advanced Study Institute on Pattern Recognition Theory and Applications (1986 Spa, Belgium)	1987	Springer-Verlag
Semi-Markov Models: Theory and Applications	Jacques Janssen	1986	Springer US
Semi-Markov models: theory and applications	International Symposium on Semi-Markov Processes and Their Applications (1984 Brussels, Belgium)	1986	Plenum Press
From Statistics to Neural Networks: Theory and Pattern Recognition Applications	Vladimir Cherkassky; Jerome H. Friedman; Harry Wechsler	1994	Springer Berlin Heidelberg
Face Recognition: From Theory to Applications	Harry Wechsler; Jonathon P. Phillips; Vicki Bruce; Francoise Fogelman Soulie; Thomas S. Huang	1998	Springer Berlin Heidelberg
Syntactic Pattern Recognition, Applications	K.S. Fu	1977	Springer Berlin Heidelberg
Applications of pattern recognition	K. S. Fu	1982	CRC Press
Hidden Markov Models: Applications to Financial Economics	Ramaprasad Bhar; Shigeyuki Hamori	2004	Springer US
Semi-Markov Models and Applications	Jacques Janssen; Nikolaos Limnios	1999	Springer US
Hidden Markov Models and Applications	Nizar Bouguila; Wentao Fan; Manar Amayri	1st ed. 2022	Springer International Publishing
Type-2 Fuzzy Graphical Models for Pattern Recognition	Jia Zeng; Zhi-Qiang Liu	2015	Springer Berlin Heidelberg
Pattern Recognition: Analysis and Applications	S. Ramakrishnan	2016	ExLi4EvA
Chemical applications of pattern recognition	Peter C. Jurs	1975	Wiley
Pattern recognition: architectures, algorithms & applications	Réjean Plamondon	1991	World Scientific
Markov Models and Linguistic Theory	Friederick J. Damerau	1971	De Gruyter Mouton
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Showing 1 to 20 of 100 entries

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Chapter	Author(s)	Book	Book Authors	Year	Publisher
Two-Dimensional Hidden Markov Models for Pattern Recognition	Janusz Bobulski; Lukasz Adrjanowicz	Artificial Intelligence and Soft Computing: 12th International Conference, ICAISC 2013, Zakopane, Poland, June 9-13, 2013, Proceedings, Part I	Leszek Rutkowski; Marcin Korytkowski; Rafal Scherer; Ryszard Tadeusiewicz; Lotfi A. Zadeh; Jacek M. Zurada	2013	Springer Berlin Heidelberg
Models for Pattern Recognition	James C. Bezdek	Pattern Recognition with Fuzzy Objective Function Algorithms	James C. Bezdek	1981	Springer US
Applications to Pattern Recognition		Introduction to Digital Speech Processing (Foundations and Trends in Signal Processing, )	Lawrence R. Rabiner, Ronald W. Schafer	2007	Now Publishers Inc
Markov models for speech recognition	Alan F. Lippman.	Spatial statistics and digital image analysis /	National Research Council Staff; Division on Engineering and Physical Sciences Staff	1991.	National Academy Press,
Markov models for speech recognition	Alan F. Lippman.	Spatial statistics and digital image analysis /	Staff, National Research Council \| National Research Council (U.S.). \| Board on Mathematical Sciences	1991.	National Academy Press,
Pattern recognition models		Computer Programming for Beginners: 3 Books in 1: Step by Step Guide to Learn Programming, Python For Beginners, Python Machine Learning	Kevin Cooper
Applications of geostatistics and Markov models for logo recognition	T. D. Pham	Document recognition and retrieval X: 22-24 January 2003, Santa Clara, California, USA /	Kanungo, Tapas.	[2003], ©2003.	SPIE,
Why Classical Models for Pattern Recognition are Not Pattern Recognition Models	Lev Goldfarb; Jaroslav Hook	International Conference on Advances in Pattern Recognition: Proceedings of ICAPR ’98, 23–25 November 1998, Plymouth, UK	Sameer Singh	1999	Springer London
Control theory for Markov models		Stochastic models for social processes	David J. Bartholomew	1973	Wiley
From pattern recognition methods to machine vision applications	Heikki Kälviäinen	Advances in Independent Component Analysis and Learning Machines	Ella Bingham; S. Kaski; Jorma Laaksonen and Jouko Lampinen	2015	Academic Press
Hidden Markov Models Theory and Applications Preface		Theory of Segmentation	Koloydenko, Alexey; Kuljus, Kristi; Lember, Jüri	2011	Intech
Nonparametric Hidden Markov Models: Principles and Applications to Speech Recognition	Edmondo Trentin	Neural Nets: 14th Italian Workshop on Neural Nets, WIRN VIETRI 2003, Vietri sul Mare, Italy, June 4-7, 2003, Revised Papers	Bruno Apolloni; Maria Marinaro; Roberto Tagliaferri	2003	Springer Berlin Heidelberg
Pattern Recognition of International Crises Using Hidden Markov Models		Political Complexity: Nonlinear Models of Politics	Diana Richards, Editor	2010	University of Michigan Press
Pattern Recognition of International Crises Using Hidden Markov Models	Philip A. Schrodt	Political complexity: nonlinear models of politics /	Doyle, Diana Richards,	[2000], ©2000.	University of Michigan Press,
Hidden Markov Models: Applications		Bioinformatics, second edition: The Machine Learning Approach	Pierre Baldi; Søren Brunak	2001	MIT Press
Hidden Markov Models: Applications		Bioinformatics: the machine learning approach /	Baldi, Pierre.; Brunak, Søren.	©1998.	MIT Press,
Applications in pattern recognition	Gabriela Cristescu; Liana Lupşa	Non-Connected Convexities and Applications	G. Cristescu; L. Lupsa	2002	Springer US
Vein Pattern Recognition Applications	Chuck Wilson	Vein Pattern Recognition: A Privacy-Enhancing Biometric	Chuck Wilson	2010	Routledge
Research Applications: Pattern Recognition	Klaus Hentschel	Mapping the Spectrum: Techniques of Visual Representation in Research and Teaching	Prof. Dr. Klaus Hentschel	2002	Oxford University Press
12. Pattern Recognition Applications		Signal processing using optics: fundamentals, devices, architectures, and applications /	Boone, Bradley G.	1998.	Oxford University Press,
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