Neuware -This unique and useful textbook presents a comprehensive review of the essentials of image data mining, and the latest cutting-edge techniques used in the field. The coverage spans all aspects of image analysis and understanding, offering deep insights into areas of feature extraction, machine learning, and image retrieval. The theoretical coverage is supported by practical mathematical models and algorithms, utilizing data from real-world examples and experiments.Topics and features:Describes essential tools for image mining, covering Fourier transforms, Gabor filters, and contemporary wavelet transformsDevelops many new exercises (most with MATLAB code and instructions)Includes review summaries at the end of each chapterAnalyses state-of-the-art models, algorithms, and procedures for image miningIntegrates new sections on pre-processing, discrete cosine transform, and statistical inference and testingDemonstrates how features like color, texture, and shape can be mined or extracted for image representationApplies powerful classification approaches: Bayesian classification, support vector machines, neural networks, and decision treesImplements imaging techniques for indexing, ranking, and presentation, as well as database visualizationThis easy-to-follow, award-winning book illuminates how concepts from fundamental and advanced mathematics can be applied to solve a broad range of image data mining problems encountered by students and researchers of computer science. Students of mathematics and other scientific disciplines will also benefit from the applications and solutions described in the text, together with the hands-on exercises that enable the reader to gain first-hand experience of computing.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 400 pp. Englisch.

Bestandsnummer des Verk�ufers 9783030692537

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Bibliografische Details

Titel: Fundamentals of Image Data Mining
Verlag: Springer International Publishing, Springer International Publishing Jun 2022
Ver�ffentlichungsdatum: 2022
Sprache: Englisch
ISBN-10: 3030692531
ISBN-13: 9783030692537
Bindung: Taschenbuch
Ausgabe: 2. Auflage
Zustand: Neu

�ber diesen Titel

Inhaltsangabe

This unique and useful textbook presents a comprehensive review of the essentials of image data mining, and the latest cutting-edge techniques used in the field. The coverage spans all aspects of image analysis and understanding, offering deep insights into areas of feature extraction, machine learning, and image retrieval. The theoretical coverage is supported by practical mathematical models and algorithms, utilizing data from real-world examples and experiments.

Topics and features:

Describes essential tools for image mining, covering Fourier transforms, Gabor filters, and contemporary wavelet transforms
Develops many new exercises (most with MATLAB code and instructions)
Includes review summaries at the end of each chapter
Analyses state-of-the-art models, algorithms, and procedures for image mining
Integrates new sections on pre-processing, discrete cosine transform, and statistical inference and testing
Demonstrates how features like color, texture, and shape can be mined or extracted for image representation
Applies powerful classification approaches: Bayesian classification, support vector machines, neural networks, and decision trees
Implements imaging techniques for indexing, ranking, and presentation, as well as database visualization

This easy-to-follow, award-winning book illuminates how concepts from fundamental and advanced mathematics can be applied to solve a broad range of image data mining problems encountered by students and researchers of computer science. Students of mathematics and other scientific disciplines will also benefit from the applications and solutions described in the text, together with the hands-on exercises that enable the reader to gain first-hand experience of computing.

�ber die Autorin bzw. den Autor

Dr. Dengsheng Zhang is Senior Lecturer in the School of Engineering, Information Technology and Physical Sciences at Federation University Australia and a Guest Professor of Xi'an University of Posts & Telecommunications, China. He is on the list of Top 2% Scientists in the World ranked by Stanford University. Dr Zhang was the Textbook & Academic Authors Association’s winner of their 2020 Most Promising New Textbook Award, with the judges noting:

“Fundamentals of Image Data Mining provides excellent coverage of current algorithms and techniques in image analysis. It does this using a progression of essential and novel image processing tools that give students an in-depth understanding of how the tools fit together and how to apply them to problems.”

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