Introduction to Statistical Pattern Recognition, Fukunaga, Keinosuke

Автор: Christopher M. Bishop
Название: Pattern Recognition and Machine Learning
ISBN: 1493938436 ISBN-13(EAN): 9781493938438
Издательство: Springer
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Цена: 69870.00 T
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Описание: Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

Автор: Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong
Название: Mathematics for Machine Learning
ISBN: 110845514X ISBN-13(EAN): 9781108455145
Издательство: Cambridge Academ
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Цена: 42230.00 T
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Описание: This self-contained textbook introduces all the relevant mathematical concepts needed to understand and use machine learning methods, with a minimum of prerequisites. Topics include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics.

Автор: Fieguth, Paul
Название: Introduction to pattern recognition and machine learning
ISBN: 3030959937 ISBN-13(EAN): 9783030959937
Издательство: Springer
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Цена: 83850.00 T
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Описание: The domains of Pattern Recognition and Machine Learning have experienced exceptional interest and growth, however the overwhelming number of methods and applications can make the fields seem bewildering.

Автор: Ortega, Antonio,
Название: Introduction to graph signal processing /
ISBN: 1108428134 ISBN-13(EAN): 9781108428132
Издательство: Cambridge Academ
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Цена: 102790.00 T
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Описание: An intuitive, accessible text explaining the fundamentals and applications of signal processing on graphs. It covers basic and advanced topics, includes numerous exercises and Matlab examples, and is accompanied online by a solutions manual for instructors, making it essential reading for graduate students, researchers, and industry professionals.

Автор: Marco Alexander Treiber
Название: An Introduction to Object Recognition
ISBN: 1447125789 ISBN-13(EAN): 9781447125785
Издательство: Springer
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Цена: 97820.00 T
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Описание: This text/reference provides a comprehensive introduction to object recognition (OR). The book presents an overview of the diverse applications for OR and highlights important algorithm classes, presenting representative example algorithms for each class.

Автор: Geoff Dougherty
Название: Pattern Recognition and Classification
ISBN: 1493953354 ISBN-13(EAN): 9781493953356
Издательство: Springer
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Цена: 83850.00 T
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Описание: This volume, both comprehensive and accessible, introduces all the key concepts in pattern recognition, and includes many examples and exercises that make it an ideal guide to an important methodology widely deployed in today`s ubiquitous automated systems.

Автор: William W. Hsieh
Название: Introduction to Environmental Data Science
ISBN: 1107065550 ISBN-13(EAN): 9781107065550
Издательство: Cambridge Academ
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Цена: 65470.00 T
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Описание: Statistical and machine learning methods have many applications in the environmental sciences, including prediction and data analysis in meteorology, hydrology and oceanography; pattern recognition for satellite images from remote sensing; management of agriculture and forests; assessment of climate change; and much more. With rapid advances in machine learning in the last decade, this book provides an urgently needed, comprehensive guide to machine learning and statistics for students and researchers interested in environmental data science. It includes intuitive explanations covering the relevant background mathematics, with examples drawn from the environmental sciences. A broad range of topics is covered, including correlation, regression, classification, clustering, neural networks, random forests, boosting, kernel methods, evolutionary algorithms and deep learning, as well as the recent merging of machine learning and physics. End?of?chapter exercises allow readers to develop their problem-solving skills, and online datasets allow readers to practise analysis of real data.

Автор: Tommaso Mansi; Kristin McLeod; Mihaela Pop; Kawal
Название: Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges
ISBN: 3319527177 ISBN-13(EAN): 9783319527178
Издательство: Springer
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Цена: 51230.00 T
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Описание: This book constitutes the thoroughly refereed post-workshop proceedings of the 7th International Workshop on Statistical Atlases and Computational Models of the Heart: Imaging and Modelling Challenges.

Автор: Addisson Salazar
Название: On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling
ISBN: 3642428754 ISBN-13(EAN): 9783642428753
Издательство: Springer
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Цена: 95770.00 T
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Описание: This outstanding review of the literature on the core theoretical foundations of applied statistical pattern recognition defines a novel mode of pattern recognition and classification, based on independent component analysis mixture modeling (ICAMM).

Автор: Sarunas Raudys
Название: Statistical and Neural Classifiers
ISBN: 1447110714 ISBN-13(EAN): 9781447110712
Издательство: Springer
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Цена: 130430.00 T
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Описание: In this book, Sarunas Raudys - an internationally respected researcher in the area - provides an excellent mathematical and applied introduction to how neural network classifiers work and how they should be used..

Автор: Oscar Camara; Tommaso Mansi; Mihaela Pop; Kawal Rh
Название: Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges
ISBN: 3642542670 ISBN-13(EAN): 9783642542671
Издательство: Springer
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Цена: 42860.00 T
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Описание: This book constitutes the thoroughly refereed post-conference proceedings of the 4th International Workshop on Statistical Atlases and Computational Models of the Heart: Imaging and Modelling Challenges, STACOM 2013, held in conjunction with MICCAI 2013, in Nagoya, Japan, in September 2013.

Автор: Terry Caelli; Adnan Amin; Robert P.W. Duin; Mohame
Название: Structural, Syntactic, and Statistical Pattern Recognition
ISBN: 3540440119 ISBN-13(EAN): 9783540440116
Издательство: Springer
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Цена: 121110.00 T
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Описание: Constitutes the proceedings of the 9th International Workshop on Structural and Syntactic Pattern Recognition and the 4th International Workshop on Statistical Techniques in Pattern Recognition held in Canada in 2002.