cunningham padraig (13 Ergebnisse)

Softcover. Zustand: Très bon. Ancien livre de bibliothèque. Edition 1998. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Very good. Former library book. Edition 1998. Ammareal gives back up to 15% of this item's net price to charity organizations.

Zustand: 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.

Zustand: New. pp. xvi + 290 98 Illus.

Zustand: New. In.

Zustand: 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.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the refereed proceedings of the 4th European Workshop on Case-Based Reasoning, EWCBR-98, held in Dublin, Ireland, in September 1998.The 41 revised full papers presented were carefully selected and reviewed for inclusion in the proceedings. The contributions address the representation and organization of cases in case-bases, the assessment of case similarity, the efficient retrieval of cases from large case-bases, the adaptation of similar case solutions to fit the current problem, case learning and case-base maintenance, and the application of CBR technology to real-world problems.

Taschenbuch. Zustand: Neu. Advances in Case-Based Reasoning | 4th European Workshop, EWCBR'98, Dublin, Ireland, September 23-25, 1998, Proceedings | Barry Smyth (u. a.) | Taschenbuch | xii | Englisch | 1998 | Springer | EAN 9783540649908 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Zustand: 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.

Zustand: New. In.

Zustand: fine. l'article peut presenter de tres legers signes d'usure, petites rayures ou imperfections esthetiques. vendeur professionnel; envoi soigne en 24/48h.

Taschenbuch. Zustand: Neu. Machine Learning Techniques for Multimedia | Case Studies on Organization and Retrieval | Matthieu Cord (u. a.) | Taschenbuch | 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.

Buch. Zustand: 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.

Taschenbuch. Zustand: 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.