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Hardcover. Condition: New. US SELLER SHIPS FAST FROM USA.
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Machine Learning Techniques for Multimedia : Case Studies on Organization and Retrieval
Book 9 of 43: Cognitive TechnologiesLanguage: English
Published by Springer Berlin / Heidelberg, 2008
ISBN 10: 354075170X ISBN 13: 9783540751700
Condition: Very Good. Former library copy. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.
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Condition: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
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Condition: New. pp. xvi + 290 1st Edition.
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Condition: New. pp. xvi + 290 98 Illus.
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Condition: New. pp. xvi + 290.
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Machine Learning Techniques For Adaptive Multimedia Retrieval: Technologies Applications And Perspectives (Premier Reference Source)
Language: English
Published by Information Science Reference, 2010
ISBN 10: 161692859X ISBN 13: 9781616928599
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Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
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Condition: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
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Machine Learning Techniques for Multimedia : Case Studies on Organization and Retrieval
Book 9 of 43: Cognitive TechnologiesUS$ 41.10 10% offUS$ 36.99
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Add to basketCondition: Sehr gut. Zustand: Sehr gut | Seiten: 308 | Sprache: Englisch | Produktart: Bücher | Processing multimedia content has emerged as a key area for the application of machine learning techniques, where the objectives are to provide insight into the domain from which the data is drawn, and to organize that data and improve the performance of the processes manipulating it. Applying machine learning techniques to multimedia content involves special considerations ¿ the data is typically of very high dimension, and the normal distinction between supervised and unsupervised techniques does not always apply. This book provides a comprehensive coverage of the most important machine learning techniques used and their application in this domain. Arising from the EU MUSCLE network, a program that drew together multidisciplinary teams with expertise in machine learning, pattern recognition, artificial intelligence, and image, video, text and crossmedia processing, the book first introduces the machine learning principles and techniques that are applied in multimedia data processing and analysis. The second part focuses on multimedia data processing applications, with chapters examining specific machine learning issues in domains such as image retrieval, biometrics, semantic labelling, mobile devices, and mining in text and music.This book will be suitable for practitioners, researchers and students engaged with machine learning in multimedia applications.
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hardcover. Condition: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
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Machine Learning Techniques for Multimedia: Case Studies on Organization and Retrieval (Cognitive Technologies)
Book 9 of 43: Cognitive TechnologiesSeller: Ria Christie Collections, Uxbridge, United Kingdom
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Machine Learning Techniques For Multimedia: Case Studies On Organization And Retrieval
Language: English
Published by Springer, 2008
Hardcover. Condition: New. ISBN:9783540751700.
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Machine Learning Techniques for Adaptive Multimedia Retrieval: Technologies Applications and Perspectives
Language: English
Published by Information Science Reference, 2010
ISBN 10: 161692859X ISBN 13: 9781616928599
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
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Machine Learning for Intelligent Multimedia Analytics: Techniques and Applications (Studies in Big Data)
Book 82 of 108: Studies in Big DataSeller: Ria Christie Collections, Uxbridge, United Kingdom
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Machine Learning for Intelligent Multimedia Analytics: Techniques and Applications (Studies in Big Data, 82)
Book 82 of 108: Studies in Big DataSeller: Ria Christie Collections, Uxbridge, United Kingdom
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Add to basketHardcover. Condition: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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Condition: fine. l'article peut presenter de tres legers signes d'usure, petites rayures ou imperfections esthetiques. vendeur professionnel; envoi soigne en 24/48h.
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Taschenbuch. Condition: Neu. Machine Learning Techniques for Multimedia | Case Studies on Organization and Retrieval | Matthieu Cord (u. a.) | Taschenbuch | Previously published in hardcover | xvi | Englisch | 2014 | Springer | EAN 9783642443626 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Machine Learning Techniques for Multimedia : Case Studies on Organization and Retrieval
Book 9 of 43: Cognitive TechnologiesLanguage: English
Published by Springer Berlin Heidelberg, Springer Berlin Heidelberg, 2008
ISBN 10: 354075170X ISBN 13: 9783540751700
Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Processing multimedia content has emerged as a key area for the application of machine learning techniques, where the objectives are to provide insight into the domain from which the data is drawn, and to organize that data and improve the performance of the processes manipulating it. Applying machine learning techniques to multimedia content involves special considerations - the data is typically of very high dimension, and the normal distinction between supervised and unsupervised techniques does not always apply. This book provides a comprehensive coverage of the most important machine learning techniques used and their application in this domain. Arising from the EU MUSCLE network, a program that drew together multidisciplinary teams with expertise in machine learning, pattern recognition, artificial intelligence, and image, video, text and crossmedia processing, the book first introduces the machine learning principles and techniques that are applied in multimedia data processing and analysis. The second part focuses on multimedia data processing applications, with chapters examining specific machine learning issues in domains such as image retrieval, biometrics, semantic labelling, mobile devices, and mining in text and music.This book will be suitable for practitioners, researchers and students engaged with machine learning in multimedia applications.
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Machine Learning Techniques for Multimedia
Book 9 of 43: Cognitive TechnologiesLanguage: English
Published by Springer Berlin Heidelberg, Springer Berlin Heidelberg Feb 2008, 2008
ISBN 10: 354075170X ISBN 13: 9783540751700
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Buch. Condition: Neu. Neuware -Processing multimedia content has emerged as a key area for the application of machine learning techniques, where the objectives are to provide insight into the domain from which the data is drawn, and to organize that data and improve the performance of the processes manipulating it. Applying machine learning techniques to multimedia content involves special considerations ¿ the data is typically of very high dimension, and the normal distinction between supervised and unsupervised techniques does not always apply.This book provides a comprehensive coverage of the most important machine learning techniques used and their application in this domain. Arising from the EU MUSCLE network, a program that drew together multidisciplinary teams with expertise in machine learning, pattern recognition, artificial intelligence, and image, video, text and crossmedia processing, the book first introduces the machine learning principles and techniques that are applied in multimedia data processing and analysis. The second part focuses on multimedia data processing applications, with chapters examining specific machine learning issues in domains such as image retrieval, biometrics, semantic labelling, mobile devices, and mining in text and music.This book will be suitable for practitioners, researchers and students engaged with machine learning in multimedia applications.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 308 pp. Englisch.
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Machine Learning Techniques for Multimedia : Case Studies on Organization and Retrieval
Book 9 of 43: Cognitive TechnologiesLanguage: English
Published by Springer, Berlin, Springer Berlin Heidelberg, Springer, 2014
ISBN 10: 3642443621 ISBN 13: 9783642443626
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Processing multimedia content has emerged as a key area for the application of machine learning techniques, where the objectives are to provide insight into the domain from which the data is drawn, and to organize that data and improve the performance of the processes manipulating it. Applying machine learning techniques to multimedia content involves special considerations - the data is typically of very high dimension, and the normal distinction between supervised and unsupervised techniques does not always apply. This book provides a comprehensive coverage of the most important machine learning techniques used and their application in this domain. Arising from the EU MUSCLE network, a program that drew together multidisciplinary teams with expertise in machine learning, pattern recognition, artificial intelligence, and image, video, text and crossmedia processing, the book first introduces the machine learning principles and techniques that are applied in multimedia data processing and analysis. The second part focuses on multimedia data processing applications, with chapters examining specific machine learning issues in domains such as image retrieval, biometrics, semantic labelling, mobile devices, and mining in text and music.This book will be suitable for practitioners, researchers and students engaged with machine learning in multimedia applications.
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Taschenbuch. Condition: Neu. Machine Learning for Intelligent Multimedia Analytics | Techniques and Applications | Pardeep Kumar (u. a.) | Taschenbuch | xiv | Englisch | 2022 | Springer | EAN 9789811594946 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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International EditionUS$ 271.13
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Add to basketCondition: New. Brand New! Fast Delivery "International Edition " and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 4-6 Working days .and we do have flat rate for up to 2LB. Extra shipping charges will be requested This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
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Machine Learning Techniques for Multimedia: Case Studies on Organization and Retrieval (Cognitive Technologies)
Book 9 of 43: Cognitive TechnologiesUS$ 259.94
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Ships from United Kingdom to U.S.A.Quantity: 1 available
Add to basketHardcover. Condition: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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Machine Learning for Intelligent Multimedia Analytics : Techniques and Applications
Book 82 of 108: Studies in Big DataLanguage: English
Published by Springer Nature Singapore, Springer Nature Singapore, 2022
ISBN 10: 9811594945 ISBN 13: 9789811594946
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents applications of machine learning techniques in processing multimedia large-scale data. Multimedia such as text, image, audio, video, and graphics stands as one of the most demanding and exciting aspects of the information era. The book discusses new challenges faced by researchers in dealing with these large-scale data and also presents innovative solutions to address several potential research problems, e.g., enabling comprehensive visual classification to fill the semantic gap by exploring large-scale data, offering a promising frontier for detailed multimedia understanding, as well as extract patterns and making effective decisions by analyzing the large collection of data.
