Deep Learning For Multimedia Processing Applications
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Deep Learning For Multimedia Processing Applications
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Author : Uzair Aslam Bhatti
language : en
Publisher: CRC Press
Release Date : 2024-02-12
Deep Learning For Multimedia Processing Applications written by Uzair Aslam Bhatti and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-12 with Computers categories.
This book 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.
Deep Learning For Multimedia Processing Applications
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Author : Uzair Aslam Bhatti
language : en
Publisher: CRC Press
Release Date : 2024-02-21
Deep Learning For Multimedia Processing Applications written by Uzair Aslam Bhatti and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-21 with Computers categories.
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.
Deep Learning For Multimedia Processing Applications
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Author : Uzair Aslam Bhatti
language : en
Publisher: CRC Press
Release Date : 2024-02-21
Deep Learning For Multimedia Processing Applications written by Uzair Aslam Bhatti and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-21 with Computers categories.
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 One begins by introducing the fundamental concepts of deep learning, providing readers with a solid foundation to understand its relevance in multimedia processing. 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.
Deep Learning For Multimedia Processing Applications
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Author : Uzair Aslam Bhatti
language : en
Publisher:
Release Date : 2024
Deep Learning For Multimedia Processing Applications written by Uzair Aslam Bhatti and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024 with categories.
Deep Learning For Multimedia Processing Applications
DOWNLOAD
Author : Uzair Aslam Bhatti
language : en
Publisher: CRC Press
Release Date : 2024-02-21
Deep Learning For Multimedia Processing Applications written by Uzair Aslam Bhatti and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-21 with Computers categories.
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 One begins by introducing the fundamental concepts of deep learning, providing readers with a solid foundation to understand its relevance in multimedia processing. 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.
Deep Learning Based Applications For Multimedia Processing Applications
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Author : Uzair Aslam Bhatti
language : en
Publisher: CRC Press
Release Date : 2024-02
Deep Learning Based Applications For Multimedia Processing Applications written by Uzair Aslam Bhatti and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02 with Computers categories.
Divided into two volumes, Volume 1 begins by introducing the fundamental concepts of deep learning, providing readers with a solid foundation to understand its relevance in multimedia processing. Volumes 2 delves into advanced topics such as convolutional neural networks, recurrent neural networks, and generative adversarial networks.
Machine Learning Techniques For Multimedia
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Author : Matthieu Cord
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-02-07
Machine Learning Techniques For Multimedia written by Matthieu Cord and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-02-07 with Computers categories.
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.
Artificial Intelligence For Multimedia Information Processing
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Author : Xavier Savarimuthu
language : en
Publisher: CRC Press
Release Date : 2024-06-14
Artificial Intelligence For Multimedia Information Processing written by Xavier Savarimuthu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-14 with Technology & Engineering categories.
Advances in artificial intelligence (AI), widespread mobile devices, internet technologies, multimedia data sources, and information processing have led to the emergence of multimedia processing. Multimedia processing is the application of signal processing tools to multimedia data—text, audio, images, and video—to allow the interpretation of these data, particularly in urban and smart city environments. This book discusses the new standards of multimedia and information processing from several technological perspectives, including analytics empowered by AI, streaming on the intelligent edge, multimedia edge caching and AI, services for edge AI, and hardware and devices for multimedia on edge intelligence. FEATURES Covers a wide spectrum of enabling technologies for AI and machine learning for multimedia and information processing Includes many applications using AI, from robotics and driverless cars to environmental, human health, and remote sensing Presents an overview of the fundamentals of AI and multimedia processing: imaging, signal, and speech Explains new models and architectures for multimedia streaming, services, and caching for AI Discusses the emerging paradigms of the deployment of hardware and devices for multimedia on edge intelligence Gives recommendations for future research in multimedia and AI This book is written for engineers and graduate students in image and signal processing, information processing, environmental engineering, medical and public health, etc., who are interested in machine learning, deep learning, and multimedia processing.
Deep Learning For Earth Observation And Climate Monitoring
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Author : Uzair Aslam Bhatti
language : en
Publisher: Elsevier
Release Date : 2025-03-19
Deep Learning For Earth Observation And Climate Monitoring written by Uzair Aslam Bhatti and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-19 with Science categories.
Deep Learning for Earth Observation and Climate Monitoring bridges the gap between deep learning and the Earth sciences, offering cutting-edge techniques and applications that are transforming our understanding of the environment. With a focus on practical scenarios, this book introduces readers to the fundamental concepts of deep learning, from classification and image segmentation to anomaly detection and domain adaptability. The book includes practical discussion on regression, parameter retrieval, forecasting, and interpolation, among other topics. With a solid foundational theory, real-world examples, and example codes, it provides a full understanding of how intelligent systems can be applied to enhance Earth observation and especially climate monitoring.This book allows readers to apply learning representations, unsupervised deep learning, and physics-aware models to Earth observation data, enabling them to leverage the power of deep learning to fully utilize the wealth of environmental data from satellite technologies. - Introduces deep learning for classification, covering recent improvements in image segmentation and encoding priors, anomaly detection and target recognition, and domain adaptability - Includes both learning representations and unsupervised deep learning, covering deep learning picture fusion, regression, parameter retrieval, forecasting, and interpolation from a practical standpoint - Provides a number of physics-aware deep learning models, including the code and the parameterization of models on a companion website, as well as links to relevant data repositories, allowing readers to test techniques themselves
Deep Learning For Multimedia Processing Predicting Media Interestingness
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Author : Lluc Cardoner Campi
language : en
Publisher:
Release Date : 2017
Deep Learning For Multimedia Processing Predicting Media Interestingness written by Lluc Cardoner Campi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.
This thesis explores the application of a deep learning approach for the prediction of media interestingness. Two different models are investigated, one for the prediction of image and one for the prediction of video interestingness. For the prediction of image interestingness, the ResNet50 network is fine-tuned to obtain best results. First, some layers are added. Next, the model is trained and fine-tuned using data augmentation, dropout, class weights, and changing other hyper parameters. For the prediction of video interestingness, first, features are extracted with a 3D convolutional network. Next a LSTM network is trained and fine-tuned with the features. The final result is a binary label for each image/video: 1 for interesting, 0 for not interesting. Additionally, a confidence value is provided for each prediction. Finally, the Mean Average Precision (MAP) is employed as evaluation metric to estimate the quality of the final results.