Machine Learning Techniques for Multimedia
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 machi...
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oai:112.137.131.14:VNU_123-257002020-06-12T08:23:44Z Machine Learning Techniques for Multimedia Cord, Matthieu Cunningham, Padraig Computer Science ; Machine learning ; 006.31 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. 2017-04-10T08:15:54Z 2017-04-10T08:15:54Z 2008 Book 9783540751700 http://repository.vnu.edu.vn/handle/VNU_123/25700 en 297 p. application/pdf Springer |
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Computer Science ; Machine learning ; 006.31 Machine Learning Techniques for Multimedia |
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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. |
author2 |
Cord, Matthieu |
author_facet |
Cord, Matthieu |
format |
Book |
title |
Machine Learning Techniques for Multimedia |
title_short |
Machine Learning Techniques for Multimedia |
title_full |
Machine Learning Techniques for Multimedia |
title_fullStr |
Machine Learning Techniques for Multimedia |
title_full_unstemmed |
Machine Learning Techniques for Multimedia |
title_sort |
machine learning techniques for multimedia |
publisher |
Springer |
publishDate |
2017 |
url |
http://repository.vnu.edu.vn/handle/VNU_123/25700 |
_version_ |
1680963554355707904 |