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Published by Taylor & Francis Ltd, 2024
ISBN 10: 1032623349 ISBN 13: 9781032623344
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Published by Taylor & Francis Ltd, London, 2024
ISBN 10: 1032623349 ISBN 13: 9781032623344
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Hardcover. Condition: new. Hardcover. 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. This book is a comprehensive guide that explores the revolutionary impact of deep learning techniques in the field of multimedia processing. Volumes Two delves into advanced topics such as convolutional neural networks, recurrent neural networks, and generative adversarial networks, explaining their unique capabilities in multimedia tasks. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Add to basketCondition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Uzair Aslam Bhatti was born in 1986. He received a PhD degree in information and communication engineering from Hainan University, Haikou, Hainan, in 2019. He completed his postdoctoral from Nanjing Normal University, Nanjing, China, in implementi.
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Add to basketBuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book is a comprehensive guide that explores the revolutionary impact of deep learning techniques in the field of multimedia processing. Volumes Two delves into advanced topics such as convolutional neural networks, recurrent neural networks, and generative adversarial networks, explaining their unique capabilities in multimedia tasks.