Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, Ingela Nystr?m; Yanio Hern?ndez Heredia; Vladimir

Автор: Strang Gilbert
Название: Linear Algebra and Learning from Data
ISBN: 0692196382 ISBN-13(EAN): 9780692196380
Издательство: Cambridge Academ
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Цена: 66520.00 T
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Описание: Linear algebra and the foundations of deep learning, together at last! From Professor Gilbert Strang, acclaimed author of Introduction to Linear Algebra, comes Linear Algebra and Learning from Data, the first textbook that teaches linear algebra together with deep learning and neural nets. This readable yet rigorous textbook contains a complete course in the linear algebra and related mathematics that students need to know to get to grips with learning from data. Included are: the four fundamental subspaces, singular value decompositions, special matrices, large matrix computation techniques, compressed sensing, probability and statistics, optimization, the architecture of neural nets, stochastic gradient descent and backpropagation.

Автор: Luis Rueda; Domingo Mery; Josef Kittler
Название: Progress in Pattern Recognition, Image Analysis and Applications
ISBN: 354076724X ISBN-13(EAN): 9783540767244
Издательство: Springer
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Цена: 111790.00 T
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Описание: Constitutes the refereed proceedings of the 12th Iberoamerican Congress on Pattern Recognition, CIARP 2007, held in Valparaiso, Chile, November 13-16, 2007. This book includes papers that cover research and mathematical methods for pattern recognition, image analysis, and applications in such diverse areas as computer vision, industry, and health.

Автор: Alberto Sanfeliu; Jos? F. Mart?nez Trinidad; Jes?s
Название: Progress in Pattern Recognition, Image Analysis and Applications
ISBN: 3540235272 ISBN-13(EAN): 9783540235279
Издательство: Springer
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Цена: 111790.00 T
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Описание: Constitutes the refereed proceedings of the 9th Iberoamerican Congress on Pattern Recognition, CIARP 2004, held in Puebla, Mexico in October 2004. This work addresses issues in pattern recognition, image analysis, and computer vision, including applications in areas like robotics, entertainment, space exploration, data mining, and others.

Автор: Jos? Ruiz-Shulcloper; Walter Kropatsch
Название: Progress in Pattern Recognition, Image Analysis and Applications
ISBN: 3540859195 ISBN-13(EAN): 9783540859192
Издательство: Springer
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Цена: 107130.00 T
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Описание: Constitutes the refereed proceedings of the 13th Iberoamerican Congress on Pattern Recognition, CIARP 2008, held in Havana, Cuba, in September 2008. This title also includes papers that are organized in sections on signal analysis for characterization and filtering, analysis of shape and texture, analysis of speech and language, and data mining.

Автор: Le Vuong Et Al
Название: Face Processing And Applications To Distance Learning
ISBN: 9814733024 ISBN-13(EAN): 9789814733021
Издательство: World Scientific Publishing
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Цена: 68640.00 T
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Описание:

This special compendium provides a concise and unified vision of facial image processing. It addresses a collection of state-of-the-art techniques, covering the most important areas for facial biometrics and behavior analysis. These techniques also converge to serve an emerging practical application of interactive distance learning.

Readers will get a broad picture of the fundamental science of the field and technical details that make the research interesting. Moreover, the intellectual investigation motivated by the demand of real-life application will make this volume an inspiring read for current and prospective researchers and engineers in the fields of computer vision, machine learning and image processing.

Автор: Bradley Efron and Trevor Hastie
Название: Computer Age Statistical Inference
ISBN: 1107149894 ISBN-13(EAN): 9781107149892
Издательство: Cambridge Academ
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Цена: 60190.00 T
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Описание: The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.

Автор: Eduardo Bayro-Corrochano; Edwin Hancock
Название: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
ISBN: 3319125672 ISBN-13(EAN): 9783319125671
Издательство: Springer
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Цена: 104350.00 T
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Описание: This book constitutes the refereed proceedings of the 19th Iberoamerican Congress on Pattern Recognition, CIARP 2014, held in Puerto Vallarta, Jalisco, Mexico, in November 2014. The papers are organized in topical sections on image coding, processing and analysis; pattern recognition and machine learning; neural networks for pattern recognition;

Автор: Jos? Ruiz-Shulcloper; Gabriella Sanniti di Baja
Название: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
ISBN: 364241821X ISBN-13(EAN): 9783642418211
Издательство: Springer
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Цена: 46570.00 T
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Описание: The papers are organized in topical sections on mathematical theory of PR, supervised and unsupervised classification, feature or instance selection for classification, image analysis and retrieval, signals analysis and processing, applications of pattern recognition, biometrics, video analysis, and data mining.

Автор: Jos? Ruiz-Shulcloper; Gabriella Sanniti di Baja
Название: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
ISBN: 3642418260 ISBN-13(EAN): 9783642418266
Издательство: Springer
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Цена: 46570.00 T
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Описание: The papers are organized in topical sections on mathematical theory of PR, supervised and unsupervised classification, feature or instance selection for classification, image analysis and retrieval, signals analysis and processing, applications of pattern recognition, biometrics, video analysis, and data mining.

Автор: Mendoza
Название: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
ISBN: 3319751921 ISBN-13(EAN): 9783319751924
Издательство: Springer
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Цена: 46570.00 T
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Описание: This book constitutes the refereed post-conference proceedings of the 22nd Iberoamerican Congress on Pattern Recognition, CIARP 2017, held in Valparaiso, Chile, in November 2017. The 87 papers presented were carefully reviewed and selected from 156 submissions.

Автор: Ruben Vera-Rodriguez; Julian Fierrez; Aythami Mora
Название: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
ISBN: 3030134687 ISBN-13(EAN): 9783030134686
Издательство: Springer
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Цена: 93160.00 T
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Описание: Machine Learning.- Data Augmentation via Variational Auto-Encoders.- LSTM-based Multi-scale Model for WindSpeed Forecasting.-Using deep learning to classify class imbalanced gene-expression microarrays datasets.-A data representation approach to support imbalanced data classification beased in TWSVM.- Improving regression models by dissimilarity representation of bio-chemical data.- A Comparative Study on Unsupervised Domain Adaption for Coffee Crop Mapping.- Analytical Comparison of Histogram Distance Measures.- Gaussian processes regression with multiple annotors.- Linear projection learned from hybrid CKA for enhancing distance-based classifiers.- Evaluation of Bag-of-Word performance for time series classification using discriminative SIFT-based mid-level representations.- Color classification methods for perennial weed detection in cereal crops.- Hierarchical graph-based segmentation in detection of object-related regions.- Dealing with heterogeneous Google Earth images on Building Area Detection task.- Evaluation of scale-aware realignments of hierarchical image segmentation.

Автор: Shalev-Shwartz
Название: Understanding Machine Learning
ISBN: 1107057132 ISBN-13(EAN): 9781107057135
Издательство: Cambridge Academ
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Цена: 74630.00 T
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Описание: Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. This book explains the principles behind the automated learning approach and the considerations underlying its usage. The authors explain the `hows` and `whys` of machine-learning algorithms, making the field accessible to both students and practitioners.