Publicado por Cham, Springer International Publishing : Imprint: Springer., 2021
ISBN 10: 3030692507 ISBN 13: 9783030692506
Idioma: Inglés
Librería: Universitätsbuchhandlung Herta Hold GmbH, Berlin, Alemania
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Añadir al carrito2nd 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.
Publicado por Springer International Publishing, 2022
ISBN 10: 3030692531 ISBN 13: 9783030692537
Idioma: Inglés
Librería: Buchpark, Trebbin, Alemania
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Añadir al carritoCondición: Sehr gut. Zustand: Sehr gut | Seiten: 400 | Sprache: Englisch | Produktart: Bücher.
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Publicado por Springer Nature Switzerland AG, 2022
ISBN 10: 3030692531 ISBN 13: 9783030692537
Idioma: Inglés
Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
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Añadir al carritoPAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.
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Publicado por Springer Nature Switzerland AG, 2022
ISBN 10: 3030692531 ISBN 13: 9783030692537
Idioma: Inglés
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Añadir al carritoPAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.
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Añadir al carritoCondición: New. pp. 314.
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Añadir al carritoCondición: New. pp. 314.
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Publicado por Springer International Publishing, Springer International Publishing, 2022
ISBN 10: 3030692531 ISBN 13: 9783030692537
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 53,49
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Añadir al carritoTaschenbuch. Condición: 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.
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Añadir al carritoPaperback or Softback. Condición: New. Fundamentals of Image Data Mining: Analysis, Features, Classification and Retrieval 1.23. Book.
Librería: Chiron Media, Wallingford, Reino Unido
EUR 49,79
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Publicado por Springer Nature Switzerland AG, CH, 2022
ISBN 10: 3030692531 ISBN 13: 9783030692537
Idioma: Inglés
Librería: Rarewaves.com UK, London, Reino Unido
EUR 65,99
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Añadir al carritoPaperback. Condición: New. Second Edition 2021. 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 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.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 54,33
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Añadir al carritoCondición: As New. Unread book in perfect condition.
Publicado por Springer Nature Switzerland AG, CH, 2022
ISBN 10: 3030692531 ISBN 13: 9783030692537
Idioma: Inglés
Librería: Rarewaves.com USA, London, LONDO, Reino Unido
EUR 71,60
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Añadir al carritoPaperback. Condición: New. Second Edition 2021. 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 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.
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 56,17
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Librería: Chiron Media, Wallingford, Reino Unido
EUR 57,18
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Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 73,05
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Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 68,86
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Publicado por Springer International Publishing, 2020
ISBN 10: 3030179915 ISBN 13: 9783030179915
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 64,19
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This reader-friendly 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 the essential tools for image mining, covering Fourier transforms, Gabor filters, and contemporary wavelet transforms; reviews a varied range of state-of-the-art models, algorithms, and procedures for image mining; emphasizes how to deal with real image data for practical image mining; highlights how such features as color, texture, and shape can be mined or extracted from images for image representation; presents four powerful approaches for classifying image data, namely, Bayesian classification, Support Vector Machines, Neural Networks, and Decision Trees; discusses techniques for indexing, image ranking, and image presentation, along with image database visualization methods; provides self-test exercises with instructions or Matlab code, as well as review summaries at the end of each chapter.This easy-to-follow work 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.
Librería: Majestic Books, Hounslow, Reino Unido
EUR 68,69
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Publicado por Springer, Berlin|Springer International Publishing|Springer, 2022
ISBN 10: 3030692531 ISBN 13: 9783030692537
Idioma: Inglés
Librería: moluna, Greven, Alemania
EUR 57,84
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Añadir al carritoCondición: New. 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 i.
Librería: Chiron Media, Wallingford, Reino Unido
EUR 69,53
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Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 71,10
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Publicado por Springer International Publishing, Springer International Publishing, 2021
ISBN 10: 3030692507 ISBN 13: 9783030692506
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 74,89
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Añadir al carritoBuch. Condición: 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.