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Face Image Analysis by Unsupervised Learning, Marian Stewart Bartlett


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Цена: 13974.00р.
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Автор: Marian Stewart Bartlett
Название:  Face Image Analysis by Unsupervised Learning
ISBN: 9781461356530
Издательство: Springer
Классификация:






ISBN-10: 1461356539
Обложка/Формат: Paperback
Страницы: 173
Вес: 0.28 кг.
Дата издания: 26.10.2012
Серия: The Springer International Series in Engineering and Computer Science
Язык: English
Размер: 234 x 156 x 10
Основная тема: Computer Science
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: Face Image Analysis by Unsupervised Learning explores adaptive approaches to image analysis.


Temporal Data Mining via Unsupervised Ensemble Learning

Автор: Yang Yun
Название: Temporal Data Mining via Unsupervised Ensemble Learning
ISBN: 0128116544 ISBN-13(EAN): 9780128116548
Издательство: Elsevier Science
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Цена: 7241.00 р.
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Описание: Temporal Data Mining via Unsupervised Ensemble Learning provides the principle knowledge of temporal data mining in association with unsupervised ensemble learning and the fundamental problems of temporal data clustering from different perspectives. By providing three proposed ensemble approaches of temporal data clustering, this book presents a practical focus of fundamental knowledge and techniques, along with a rich blend of theory and practice. . Furthermore, the book includes illustrations of the proposed approaches based on data and simulation experiments to demonstrate all methodologies, and is a guide to the proper usage of these methods. As there is nothing universal that can solve all problems, it is important to understand the characteristics of both clustering algorithms and the target temporal data so the correct approach can be selected for a given clustering problem. . Scientists, researchers, and data analysts working with machine learning and data mining will benefit from this innovative book, as will undergraduate and graduate students following courses in computer science, engineering, and statistics.

Fusion Methods for Unsupervised Learning Ensembles

Автор: Bruno Baruque
Название: Fusion Methods for Unsupervised Learning Ensembles
ISBN: 3642423280 ISBN-13(EAN): 9783642423284
Издательство: Springer
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Цена: 18167.00 р.
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Описание: This book examines the potential of the ensemble meta-algorithm by describing and testing a technique based on the combination of ensembles and statistical PCA that is able to determine the presence of outliers in high-dimensional data sets.

Dimensionality Reduction with Unsupervised Nearest Neighbors

Автор: Oliver Kramer
Название: Dimensionality Reduction with Unsupervised Nearest Neighbors
ISBN: 3642386512 ISBN-13(EAN): 9783642386510
Издательство: Springer
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Цена: 19591.00 р.
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Описание: This book is devoted to a novel approach for dimensionality reduction based on the famous nearest neighbor method that is a powerful classification and regression approach.

Applications of Supervised and Unsupervised Ensemble Methods

Автор: Oleg Okun
Название: Applications of Supervised and Unsupervised Ensemble Methods
ISBN: 3642039987 ISBN-13(EAN): 9783642039980
Издательство: Springer
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Цена: 20962.00 р.
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Описание: Expanding upon presentations at last year`s SUEMA (Supervised and Unsupervised Ensemble Methods and Applications) meeting, this volume explores recent developments in the field. Useful examples act as a guide for practitioners in computational intelligence.

Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support

Автор: M. Jorge Cardoso; Tal Arbel; Gustavo Carneiro; Tan
Название: Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support
ISBN: 3319675575 ISBN-13(EAN): 9783319675572
Издательство: Springer
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Цена: 9083.00 р.
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Описание:

This book constitutes the refereed joint proceedings of the Third International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2017, and the 6th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Quebec City, QC, Canada, in September 2017.

The 38 full papers presented at DLMIA 2017 and the 5 full papers presented at ML-CDS 2017 were carefully reviewed and selected. The DLMIA papers focus on the design and use of deep learning methods in medical imaging. The ML-CDS papers discuss new techniques of multimodal mining/retrieval and their use in clinical decision support.

Marginal Space Learning for Medical Image Analysis

Автор: Yefeng Zheng; Dorin Comaniciu
Название: Marginal Space Learning for Medical Image Analysis
ISBN: 1493955756 ISBN-13(EAN): 9781493955756
Издательство: Springer
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Цена: 11179.00 р.
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Описание: Automatic detection and segmentation of anatomical structures in medical images are prerequisites to subsequent image measurements and disease quantification, and therefore have multiple clinical applications.

Unsupervised Classification

Автор: Sanghamitra Bandyopadhyay; Sriparna Saha
Название: Unsupervised Classification
ISBN: 3642428363 ISBN-13(EAN): 9783642428364
Издательство: Springer
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Цена: 6981.00 р.
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Описание: This book offers a theoretical analysis of symmetry-based clustering techniques. It includes extensive real-world applications in data mining, remote sensing imaging, MR brain imaging, gene expression data analysis, and face detection.

Marginal Space Learning for Medical Image Analysis

Автор: Zheng
Название: Marginal Space Learning for Medical Image Analysis
ISBN: 1493905996 ISBN-13(EAN): 9781493905997
Издательство: Springer
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Цена: 11179.00 р.
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Описание: Automatic detection and segmentation of anatomical structures in medical images are prerequisites to subsequent image measurements and disease quantification, and therefore have multiple clinical applications.

Supervised and Unsupervised Ensemble Methods and their Applications

Автор: Oleg Okun
Название: Supervised and Unsupervised Ensemble Methods and their Applications
ISBN: 3540789804 ISBN-13(EAN): 9783540789802
Издательство: Springer
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Цена: 20962.00 р.
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Описание: Ensembles of Clustering Methods and Their Applications.- Cluster Ensemble Methods: from Single Clusterings to Combined Solutions.- Random Subspace Ensembles for Clustering Categorical Data.- Ensemble Clustering with a Fuzzy Approach.- Collaborative Multi-Strategical Clustering for Object-Oriented Image Analysis.- Ensembles of Classification Methods and Their Applications.- Intrusion Detection in Computer Systems Using Multiple Classifier Systems.- Ensembles of Nearest Neighbors for Gene Expression Based Cancer Classification.- Multivariate Time Series Classification via Stacking of Univariate Classifiers.- Gradient Boosting GARCH and Neural Networks for Time Series Prediction.- Cascading with VDM and Binary Decision Trees for Nominal Data.- Erratum.

Dimensionality Reduction with Unsupervised Nearest Neighbors

Автор: Oliver Kramer
Название: Dimensionality Reduction with Unsupervised Nearest Neighbors
ISBN: 3662518953 ISBN-13(EAN): 9783662518953
Издательство: Springer
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Цена: 16977.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book is devoted to a novel approach for dimensionality reduction based on the famous nearest neighbor method that is a powerful classification and regression approach.

Statistical Learning and Pattern Analysis for Image and Video Processing

Автор: Nanning Zheng; Jianru Xue
Название: Statistical Learning and Pattern Analysis for Image and Video Processing
ISBN: 1447126734 ISBN-13(EAN): 9781447126737
Издательство: Springer
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Цена: 23058.00 р.
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Описание: This textbook is an overview of theories, methodologies, and recent developments in the field, covering the theoretical foundation and providing a complete summary of the latest advances. It also presents key issues to be considered in making a real system.


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