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Fundamentals of Image Data Mining: Analysis, Features, Classification and Retrieval - Couverture rigide
Synopsis
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.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l?auteur
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."
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Fundamentals of Image Data Mining. Analysis, Features, Classification and Retrieval. By Dengsheng Zhang.
Edité par
Cham, Springer International Publishing : Imprint: Springer., 2021
ISBN 10 : 3030692507
ISBN 13 : 9783030692506
Ancien ou d'occasion
Couverture rigide
Vendeur : Universitätsbuchhandlung Herta Hold GmbH, Berlin, Allemagne
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2nd ed. 2021. XXXIII, 363 p. Hardcover. 2nd ed. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Texts in Computer Science. Sprache: Englisch. N° de réf. du vendeur 8122IB
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Fundamentals of Image Data Mining
Edité par
Springer International Publishing, 2021
ISBN 10 : 3030692507
ISBN 13 : 9783030692506
Neuf
Couverture rigide
Vendeur : moluna, Greven, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Gebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents a complete introduction to image data mining, and a treasure trove of cutting-edge techniques in image data mining Describes the applied mathematics and mathematical modeling in an engaging style, complete with an accessible introduc. N° de réf. du vendeur 458552673
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Fundamentals of Image Data Mining : Analysis, Features, Classification and Retrieval
ISBN 10 : 3030692507
ISBN 13 : 9783030692506
Neuf
Couverture rigide
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 transformsDevelopsmanynew 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 miningIntegratesnewsectionson 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. N° de réf. du vendeur 9783030692506
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Fundamentals of Image Data Mining
Edité par
Springer International Publishing Jun 2021, 2021
ISBN 10 : 3030692507
ISBN 13 : 9783030692506
Neuf
Couverture rigide
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - 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 transformsDevelopsmanynew 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 miningIntegratesnewsectionson 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. 400 pp. Englisch. N° de réf. du vendeur 9783030692506
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Fundamentals of Image Data Mining
ISBN 10 : 3030692507
ISBN 13 : 9783030692506
Neuf
Couverture rigide
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. 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. N° de réf. du vendeur 9783030692506
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