Machine Learning For Multimedia Content Analysis

Author : Yihong Gong
Publisher : Springer Science & Business Media
ISBN 13 : 0387699422
Total Pages : 282 pages
Book Rating : 4.24/5 ( download)

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Download or read book Machine Learning for Multimedia Content Analysis written by Yihong Gong and published by Springer Science & Business Media. This book was released on 2007-09-26 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume introduces machine learning techniques that are particularly powerful and effective for modeling multimedia data and common tasks of multimedia content analysis. It systematically covers key machine learning techniques in an intuitive fashion and demonstrates their applications through case studies. Coverage includes examples of unsupervised learning, generative models and discriminative models. In addition, the book examines Maximum Margin Markov (M3) networks, which strive to combine the advantages of both the graphical models and Support Vector Machines (SVM).

Author : Matthieu Cord
Publisher : Springer Science & Business Media
ISBN 13 : 3540751718
Total Pages : 297 pages
Book Rating : 4.17/5 ( download)

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Download or read book Machine Learning Techniques for Multimedia written by Matthieu Cord and published by Springer Science & Business Media. This book was released on 2008-02-07 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. Arising from the EU MUSCLE network, this multidisciplinary book provides a comprehensive coverage of the most important machine learning techniques used and their application in this domain.

Author : Francesco Camastra
Publisher : Springer
ISBN 13 : 144716735X
Total Pages : 561 pages
Book Rating : 4.58/5 ( download)

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Download or read book Machine Learning for Audio, Image and Video Analysis written by Francesco Camastra and published by Springer. This book was released on 2015-07-21 with total page 561 pages. Available in PDF, EPUB and Kindle. Book excerpt: This second edition focuses on audio, image and video data, the three main types of input that machines deal with when interacting with the real world. A set of appendices provides the reader with self-contained introductions to the mathematical background necessary to read the book. Divided into three main parts, From Perception to Computation introduces methodologies aimed at representing the data in forms suitable for computer processing, especially when it comes to audio and images. Whilst the second part, Machine Learning includes an extensive overview of statistical techniques aimed at addressing three main problems, namely classification (automatically assigning a data sample to one of the classes belonging to a predefined set), clustering (automatically grouping data samples according to the similarity of their properties) and sequence analysis (automatically mapping a sequence of observations into a sequence of human-understandable symbols). The third part Applications shows how the abstract problems defined in the second part underlie technologies capable to perform complex tasks such as the recognition of hand gestures or the transcription of handwritten data. Machine Learning for Audio, Image and Video Analysis is suitable for students to acquire a solid background in machine learning as well as for practitioners to deepen their knowledge of the state-of-the-art. All application chapters are based on publicly available data and free software packages, thus allowing readers to replicate the experiments.

Author : Zechao Li
Publisher : Springer
ISBN 13 : 9811036896
Total Pages : 156 pages
Book Rating : 4.97/5 ( download)

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Download or read book Understanding-Oriented Multimedia Content Analysis written by Zechao Li and published by Springer. This book was released on 2017-05-26 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a systematic introduction to an understanding-oriented approach to multimedia content analysis. It integrates the visual understanding and learning models into a unified framework, within which the visual understanding guides the model learning while the learned models improve the visual understanding. More specifically, it discusses multimedia content representations and analysis including feature selection, feature extraction, image tagging, user-oriented tag recommendation and understanding-oriented multimedia applications. The book was nominated by the University of Chinese Academy of Sciences and China Computer Federation as an outstanding PhD thesis. By providing the fundamental technologies and state-of-the-art methods, it is a valuable resource for graduate students and researchers working in the field computer vision and machine learning.

Author : Pardeep Kumar
Publisher : Springer Nature
ISBN 13 : 9811594929
Total Pages : 341 pages
Book Rating : 4.22/5 ( download)

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Download or read book Machine Learning for Intelligent Multimedia Analytics written by Pardeep Kumar and published by Springer Nature. This book was released on 2021-01-16 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Author : Uzair Aslam Bhatti
Publisher : CRC Press
ISBN 13 : 1003828051
Total Pages : 481 pages
Book Rating : 4.51/5 ( download)

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Download or read book Deep Learning for Multimedia Processing Applications written by Uzair Aslam Bhatti and published by CRC Press. This book was released on 2024-02-21 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning for Multimedia Processing Applications is a comprehensive guide that explores the revolutionary impact of deep learning techniques in the field of multimedia processing. Written for a wide range of readers, from students to professionals, this book offers a concise and accessible overview of the application of deep learning in various multimedia domains, including image processing, video analysis, audio recognition, and natural language processing. Divided into two volumes, Volume Two delves into advanced topics such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs), explaining their unique capabilities in multimedia tasks. Readers will discover how deep learning techniques enable accurate and efficient image recognition, object detection, semantic segmentation, and image synthesis. The book also covers video analysis techniques, including action recognition, video captioning, and video generation, highlighting the role of deep learning in extracting meaningful information from videos. Furthermore, the book explores audio processing tasks such as speech recognition, music classification, and sound event detection using deep learning models. It demonstrates how deep learning algorithms can effectively process audio data, opening up new possibilities in multimedia applications. Lastly, the book explores the integration of deep learning with natural language processing techniques, enabling systems to understand, generate, and interpret textual information in multimedia contexts. Throughout the book, practical examples, code snippets, and real-world case studies are provided to help readers gain hands-on experience in implementing deep learning solutions for multimedia processing. Deep Learning for Multimedia Processing Applications is an essential resource for anyone interested in harnessing the power of deep learning to unlock the vast potential of multimedia data.

Author : Ying Li
Publisher : Springer Science & Business Media
ISBN 13 : 1475737122
Total Pages : 226 pages
Book Rating : 4.27/5 ( download)

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Download or read book Video Content Analysis Using Multimodal Information written by Ying Li and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: Video Content Analysis Using Multimodal Information For Movie Content Extraction, Indexing and Representation is on content-based multimedia analysis, indexing, representation and applications with a focus on feature films. Presented are the state-of-art techniques in video content analysis domain, as well as many novel ideas and algorithms for movie content analysis based on the use of multimodal information. The authors employ multiple media cues such as audio, visual and face information to bridge the gap between low-level audiovisual features and high-level video semantics. Based on sophisticated audio and visual content processing such as video segmentation and audio classification, the original video is re-represented in the form of a set of semantic video scenes or events, where an event is further classified as a 2-speaker dialog, a multiple-speaker dialog, or a hybrid event. Moreover, desired speakers are simultaneously identified from the video stream based on either a supervised or an adaptive speaker identification scheme. All this information is then integrated together to build the video's ToC (table of content) as well as the index table. Finally, a video abstraction system, which can generate either a scene-based summary or an event-based skim, is presented by exploiting the knowledge of both video semantics and video production rules. This monograph will be of great interest to research scientists and graduate level students working in the area of content-based multimedia analysis, indexing, representation and applications as well s its related fields.

Author : Irene Amerini
Publisher :
ISBN 13 : 9781680838541
Total Pages : 166 pages
Book Rating : 4.47/5 ( download)

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Download or read book Deep Learning for Multimedia Forensics written by Irene Amerini and published by . This book was released on 2021-08-31 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this survey, the latest trends and deep-learning-based techniques for multimedia forensics are introduced, in both architectural and data-processing. The publication is intended for researchers, students and professionals active in the fields of Deep Learning and Multimedia Forensics.

Author : Yiannis Kompatsiaris
Publisher : CRC Press
ISBN 13 : 1466559128
Total Pages : 676 pages
Book Rating : 4.27/5 ( download)

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Download or read book TV Content Analysis written by Yiannis Kompatsiaris and published by CRC Press. This book was released on 2012-03-19 with total page 676 pages. Available in PDF, EPUB and Kindle. Book excerpt: The rapid advancement of digital multimedia technologies has not only revolutionized the production and distribution of audiovisual content, but also created the need to efficiently analyze TV programs to enable applications for content managers and consumers. Leaving no stone unturned, TV Content Analysis: Techniques and Applications provides a de

Author : Wahiba Ben Abdessalem Karaa
Publisher : CRC Press
ISBN 13 : 1315399733
Total Pages : 227 pages
Book Rating : 4.37/5 ( download)

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Download or read book Mining Multimedia Documents written by Wahiba Ben Abdessalem Karaa and published by CRC Press. This book was released on 2017-04-21 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: The information age has led to an explosion in the amount of information available to the individual and the means by which it is accessed, stored, viewed, and transferred. In particular, the growth of the internet has led to the creation of huge repositories of multimedia documents in a diverse range of scientific and professional fields, as well as the tools to extract useful knowledge from them. Mining Multimedia Documents is a must-read for researchers, practitioners, and students working at the intersection of data mining and multimedia applications. It investigates various techniques related to mining multimedia documents based on text, image, and video features. It provides an insight into the open research problems benefitting advanced undergraduates, graduate students, researchers, scientists and practitioners in the fields of medicine, biology, production, education, government, national security and economics.