Artificial Intelligence For Multimedia Information Processing

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Artificial Intelligence for Multimedia Information Processing

Artificial Intelligence for Multimedia Information Processing
Author :
Publisher : CRC Press
Total Pages : 343
Release :
ISBN-10 : 9781040037324
ISBN-13 : 1040037321
Rating : 4/5 (321 Downloads)

Book Synopsis Artificial Intelligence for Multimedia Information Processing by : Xavier Savarimuthu

Download or read book Artificial Intelligence for Multimedia Information Processing written by Xavier Savarimuthu and published by CRC Press. This book was released on 2024-06-14 with total page 343 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.


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