Автор: Alex Pappachen James Название: Deep learning classifiers with memristive networks. ISBN: 3030145220 ISBN-13(EAN): 9783030145224 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: At first, the book offers an overview of neuro-memristive systems, including memristor devices, models, and theory, as well as an introduction to deep learning neural networks such as multi-layer networks, convolution neural networks, hierarchical temporal memory, and long short term memories, and deep neuro-fuzzy networks.
Автор: Ortega, Antonio, Название: Introduction to graph signal processing / ISBN: 1108428134 ISBN-13(EAN): 9781108428132 Издательство: Cambridge Academ Рейтинг: Цена: 15418.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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: Fieguth, Paul Название: Introduction to pattern recognition and machine learning ISBN: 3030959937 ISBN-13(EAN): 9783030959937 Издательство: Springer Рейтинг: Цена: 12577.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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: Friedhelm Schwenker; Fabio Roli; Josef Kittler Название: Multiple Classifier Systems ISBN: 3319202472 ISBN-13(EAN): 9783319202471 Издательство: Springer Рейтинг: Цена: 6708.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the refereed proceedings of the 12th International Workshop on Multiple Classifier Systems, MCS 2015, held in Gunzburg, Germany, in June/July 2015. The papers address issues in multiple classifier systems and ensemble methods, including pattern recognition, machine learning, neural network, data mining and statistics.
Автор: Sergios Theodoridis Название: Introduction to Pattern Recognition: A Matlab Approach, ISBN: 0123744865 ISBN-13(EAN): 9780123744869 Издательство: Elsevier Science Рейтинг: Цена: 5557.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An accompanying manual to "Theodoridis/Koutroumbas, Pattern Recognition", that includes Matlab code of the most common methods and algorithms in the book, together with a descriptive summary and solved examples, and including real-life data sets in imaging and audio recognition.
Автор: Vershynin, Roman (university Of Michigan, Ann Arbor) Название: Cambridge series in statistical and probabilistic mathematics ISBN: 1108415199 ISBN-13(EAN): 9781108415194 Издательство: Cambridge Academ Рейтинг: Цена: 9029.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The data sciences are moving fast, and probabilistic methods are both the foundation and a driver. This highly motivated text brings beginners up to speed quickly and provides working data scientists with powerful new tools. Ideal for a basic second course in probability with a view to data science applications, it is also suitable for self-study.
Автор: Fukunaga, Keinosuke Название: Introduction to Statistical Pattern Recognition ISBN: 0122698517 ISBN-13(EAN): 9780122698514 Издательство: Elsevier Science Рейтинг: Цена: 8420.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: A. Ardeshir Goshtasby Название: Image Registration ISBN: 1447157990 ISBN-13(EAN): 9781447157991 Издательство: Springer Рейтинг: Цена: 21661.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents a detailed guide to image registration. It details the principles behind a vast array of tools and methods as well as compares their performances using synthetic and real data.
Автор: Sarunas Raudys Название: Statistical and Neural Classifiers ISBN: 1447110714 ISBN-13(EAN): 9781447110712 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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: Ludmila I. Kuncheva Название: Combining Pattern Classifiers: Methods and Algorithms ISBN: 1118315235 ISBN-13(EAN): 9781118315231 Издательство: Wiley Рейтинг: Цена: 15674.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Combined classifiers, which are central to the ubiquitous performance of pattern recognition and machine learning, are generally considered more accurate than single classifiers.
Описание: This book contains select chapters on support vector algorithms from different perspectives, including mathematical background, properties of various kernel functions, and several applications. The main focus of this book is on orthogonal kernel functions, and the properties of the classical kernel functions—Chebyshev, Legendre, Gegenbauer, and Jacobi—are reviewed in some chapters. Moreover, the fractional form of these kernel functions is introduced in the same chapters, and for ease of use for these kernel functions, a tutorial on a Python package named ORSVM is presented. The book also exhibits a variety of applications for support vector algorithms, and in addition to the classification, these algorithms along with the introduced kernel functions are utilized for solving ordinary, partial, integro, and fractional differential equations. On the other hand, nowadays, the real-time and big data applications of support vector algorithms are growing. Consequently, the Compute Unified Device Architecture (CUDA) parallelizing the procedure of support vector algorithms based on orthogonal kernel functions is presented. The book sheds light on how to use support vector algorithms based on orthogonal kernel functions in different situations and gives a significant perspective to all machine learning and scientific machine learning researchers all around the world to utilize fractional orthogonal kernel functions in their pattern recognition or scientific computing problems.
Автор: Zhi-Hua Zhou; Fabio Roli; Josef Kittler Название: Multiple Classifier Systems ISBN: 3642380662 ISBN-13(EAN): 9783642380662 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the refereed proceedings of the 11th International Workshop on Multiple Classifier Systems, MCS 2013, held in Nanjing, China, in May 2013. The papers address issues in multiple classifier systems and ensemble methods, including pattern recognition, machine learning, neural network, data mining and statistics.
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