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Paperback. Condition: new. Paperback. Cloud based Multi-Modal Information Analytics: A Hands-on Approach discusses the various modalities of data and provide an aggregated solution using cloud. It includes the fundamentals of neural networks, different types and how they can be used for the multi-modal information analytics. The various application areas that are image-centric and videos are also presented with deployment solutions in the cloud. Features Life cycle of the multi- modal data analytics is discussed with applications of modalities of text, image, and video. Deep Learning fundamentals and architectures covering convolutional Neural Networks, recurrremt neural networks, and types of learning for different multi-modal networks. Applications of Multi-Modal Analytics covering Text , Speech, and Image. This book is aimed at researchers in Multi-modal analytics and related areas The text discusses various modalities of data and provides aggregated solutions using cloud. It includes the fundamentals of neural networks, different types and how it can be used for the multi-modal information analytics. Various image-centric and video application areas are presented with deployment solutions in the cloud. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Published by Chapman and Hall/CRC, 2025
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Add to basketPaperback. Condition: new. Paperback. Cloud based Multi-Modal Information Analytics: A Hands-on Approach discusses the various modalities of data and provide an aggregated solution using cloud. It includes the fundamentals of neural networks, different types and how they can be used for the multi-modal information analytics. The various application areas that are image-centric and videos are also presented with deployment solutions in the cloud. Features Life cycle of the multi- modal data analytics is discussed with applications of modalities of text, image, and video. Deep Learning fundamentals and architectures covering convolutional Neural Networks, recurrremt neural networks, and types of learning for different multi-modal networks. Applications of Multi-Modal Analytics covering Text , Speech, and Image. This book is aimed at researchers in Multi-modal analytics and related areas The text discusses various modalities of data and provides aggregated solutions using cloud. It includes the fundamentals of neural networks, different types and how it can be used for the multi-modal information analytics. Various image-centric and video application areas are presented with deployment solutions in the cloud. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Add to basketPaperback. Condition: new. Paperback. Cloud based Multi-Modal Information Analytics: A Hands-on Approach discusses the various modalities of data and provide an aggregated solution using cloud. It includes the fundamentals of neural networks, different types and how they can be used for the multi-modal information analytics. The various application areas that are image-centric and videos are also presented with deployment solutions in the cloud. Features Life cycle of the multi- modal data analytics is discussed with applications of modalities of text, image, and video. Deep Learning fundamentals and architectures covering convolutional Neural Networks, recurrremt neural networks, and types of learning for different multi-modal networks. Applications of Multi-Modal Analytics covering Text , Speech, and Image. This book is aimed at researchers in Multi-modal analytics and related areas The text discusses various modalities of data and provides aggregated solutions using cloud. It includes the fundamentals of neural networks, different types and how it can be used for the multi-modal information analytics. Various image-centric and video application areas are presented with deployment solutions in the cloud. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Hardcover. Condition: new. Hardcover. Cloud based Multi-Modal Information Analytics: A Hands-on Approach discusses the various modalities of data and provide an aggregated solution using cloud. It includes the fundamentals of neural networks, different types and how they can be used for the multi-modal information analytics. The various application areas that are image-centric and videos are also presented with deployment solutions in the cloud. Features Life cycle of the multi- modal data analytics is discussed with applications of modalities of text, image, and video. Deep Learning fundamentals and architectures covering convolutional Neural Networks, recurrremt neural networks, and types of learning for different multi-modal networks. Applications of Multi-Modal Analytics covering Text , Speech, and Image. This book is aimed at researchers in Multi-modal analytics and related areas The text discusses various modalities of data and provides aggregated solutions using cloud. It includes the fundamentals of neural networks, different types and how it can be used for the multi-modal information analytics. Various image-centric and video application areas are presented with deployment solutions in the cloud. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Published by Chapman and Hall/CRC, 2023
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Add to basketBuch. Condition: Neu. Neuware - The text discusses various modalities of data and provides aggregated solutions using cloud. It includes the fundamentals of neural networks, different types and how it can be used for the multi-modal information analytics. Various image-centric and video application areas are presented with deployment solutions in the cloud.
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Published by Chapman and Hall/CRC, 2023
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Add to basketGebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Dr. Srinidhi Hiriyannaiah is working as senior software engineering in GE Healthcare, he received his Ph.D. degree from VTU during 2020 and did his Master of Technology in Software Engineering from M.S. Ramaiah Institute of Technology, B.
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