Machine learning techniques multimedia (18 Ergebnisse)

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. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

hardcover. Zustand: Befriedigend. 305 Seiten; 9783540751700.4 Gewicht in Gramm: 1.

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Hardcover. Zustand: Brand New. 350 pages. 6.14x2.00x9.21 inches. In Stock.

Zustand: New. In English.

Zustand: New. In English.

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.…

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.…

Zustand: New. In English.

Zustand: New. In English.

Taschenbuch. Zustand: Neu. Machine Learning for Intelligent Multimedia Analytics | Techniques and Applications | Pardeep Kumar (u. a.) | Taschenbuch | Studies in Big Data | 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. …

Zustand: gut. 2008. Machine Learning Techniques for Multimedia: Case Studies on Organization and Retrieval (Cognitive Technologies) In deutscher Sprache. pages.

Taschenbuch. Zustand: 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.…

Buch. Zustand: 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.…

Buch. Zustand: Neu. Neuware - We are living in an AI and data-driven era. A huge volume of data is generated from all sectors including smart cities, intelligent transportation systems, smart healthcare, education, smart agriculture and smart industrial processes. This information comprises multiple modalities such as textual data, images, sound, gestures and genetic sequences, which are generated through various sources. The internet of multimedia things (IoMT) is one of the key contributors to the collection, analysis and management of voluminous multimodal data. The dominating features of IoMTs are well-timed delivery of data and dependability, but they require high levels of memory and computational power, which requires higher bandwidth and more power. Therefore, they require rigorous quality of service (QoS) and efficient, reliable and secure network frameworks. The objective of this book is to explore machine learning (ML) and deep learning (DL) techniques for securing data with multiple modalities in a wide range of data-centric smart applications in the IoMT framework. In all data-centric application domains where on-time availability of data and reliability are the major concerns, IoMT is contributing significantly. The authors present the challenges faced to organize and process multimodal data in data-centric applications, several types of data modalities, and innovative IoMT frameworks. A particular focus is placed on the role of ML and DL techniques in securing multi-modal data for real-time monitoring in smart environment applications. Machine Learning and Deep Learning Driven Techniques for Multimodal Data Security in the Internet of Multimedia Things caters to the needs of AI, big data and IoT advanced students, academic and industry researchers, engineers, security experts, data analysts, and AI and data-centric application developers.…

Hardcover. Zustand: Brand New. 349 pages. 9.25x6.10x0.81 inches. In Stock.