Srinidhi Hiriyannaiah – författare

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

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

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