Deep learning for multimedia processing applications Volume two: Signal processing and pattern recognition
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 overv...
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2024
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520 | |a 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. | ||
650 | 0 | |a Multimedia systems |x Data processing | |
650 | 0 | |a Deep learning (Machine learning) | |
650 | 0 | |a Digital video | |
650 | 0 | |a Signal processing | |
650 | 0 | |a Pattern recognition systems | |
650 | 4 | |a Multimédia ; Informatique | |
650 | 4 | |a Apprentissage profond | |
650 | 4 | |a Vidéo numérique | |
650 | 4 | |a Traitement du signal | |
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650 | 4 | |a COMPUTERS / Neural Networks | |
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spelling | Deep learning for multimedia processing applications Volume two: Signal processing and pattern recognition edited by Uzair Aslam Bhatti, Jingbing Li, Mengxing Huang, Sibghat Ullah Bazai, and Muhammad Aamir Signal processing and pattern recognition First edition. Boca Raton, FL CRC Press 2024 ©2024 1 online resource (xxv, 454 pages) illustrations (some color) Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Includes bibliographical references and index. - Description based on online resource; title from digital title page (viewed on April 04, 2024) 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. Multimedia systems Data processing Deep learning (Machine learning) Digital video Signal processing Pattern recognition systems Multimédia ; Informatique Apprentissage profond Vidéo numérique Traitement du signal Reconnaissance des formes (Informatique) COMPUTERS / Neural Networks COMPUTERS / Interactive & Multimedia COMPUTERS / Computer Science Bhatti, Uzair Aslam 1986- HerausgeberIn edt Li, Jingbing HerausgeberIn edt Mengxing, Huang HerausgeberIn edt Bazai, Sibghat Ullah HerausgeberIn edt Aamir, Muhammad HerausgeberIn edt TUM01 ZDB-30-ORH TUM_PDA_ORH https://learning.oreilly.com/library/view/-/9781003828082/?ar X:ORHE Aggregator lizenzpflichtig Volltext |
spellingShingle | Deep learning for multimedia processing applications Volume two: Signal processing and pattern recognition Multimedia systems Data processing Deep learning (Machine learning) Digital video Signal processing Pattern recognition systems Multimédia ; Informatique Apprentissage profond Vidéo numérique Traitement du signal Reconnaissance des formes (Informatique) COMPUTERS / Neural Networks COMPUTERS / Interactive & Multimedia COMPUTERS / Computer Science |
title | Deep learning for multimedia processing applications Volume two: Signal processing and pattern recognition |
title_alt | Signal processing and pattern recognition |
title_auth | Deep learning for multimedia processing applications Volume two: Signal processing and pattern recognition |
title_exact_search | Deep learning for multimedia processing applications Volume two: Signal processing and pattern recognition |
title_full | Deep learning for multimedia processing applications Volume two: Signal processing and pattern recognition edited by Uzair Aslam Bhatti, Jingbing Li, Mengxing Huang, Sibghat Ullah Bazai, and Muhammad Aamir |
title_fullStr | Deep learning for multimedia processing applications Volume two: Signal processing and pattern recognition edited by Uzair Aslam Bhatti, Jingbing Li, Mengxing Huang, Sibghat Ullah Bazai, and Muhammad Aamir |
title_full_unstemmed | Deep learning for multimedia processing applications Volume two: Signal processing and pattern recognition edited by Uzair Aslam Bhatti, Jingbing Li, Mengxing Huang, Sibghat Ullah Bazai, and Muhammad Aamir |
title_short | Deep learning for multimedia processing applications |
title_sort | deep learning for multimedia processing applications volume two signal processing and pattern recognition |
title_sub | Volume two: Signal processing and pattern recognition |
topic | Multimedia systems Data processing Deep learning (Machine learning) Digital video Signal processing Pattern recognition systems Multimédia ; Informatique Apprentissage profond Vidéo numérique Traitement du signal Reconnaissance des formes (Informatique) COMPUTERS / Neural Networks COMPUTERS / Interactive & Multimedia COMPUTERS / Computer Science |
topic_facet | Multimedia systems Data processing Deep learning (Machine learning) Digital video Signal processing Pattern recognition systems Multimédia ; Informatique Apprentissage profond Vidéo numérique Traitement du signal Reconnaissance des formes (Informatique) COMPUTERS / Neural Networks COMPUTERS / Interactive & Multimedia COMPUTERS / Computer Science |
url | https://learning.oreilly.com/library/view/-/9781003828082/?ar |
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