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portada Machine Learning Methods for Signal, Image and Speech Processing (River Publishers Series in Signal, Image and Speech Processing) (in English)
Type
Physical Book
Year
2021
Language
English
Pages
256
Format
Hardcover
Dimensions
23.4 x 15.6 x 1.6 cm
Weight
0.54 kg.
ISBN13
9788770223690

Machine Learning Methods for Signal, Image and Speech Processing (River Publishers Series in Signal, Image and Speech Processing) (in English)

Sheng-Lung Peng (Author) · M. A. Jabbar (Author) · MVV Prasad Kantipudi (Author) · River Publishers · Hardcover

Machine Learning Methods for Signal, Image and Speech Processing (River Publishers Series in Signal, Image and Speech Processing) (in English) - Jabbar, M. A. ; Kantipudi, MVV Prasad ; Peng, Sheng-Lung

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Synopsis "Machine Learning Methods for Signal, Image and Speech Processing (River Publishers Series in Signal, Image and Speech Processing) (in English)"

The signal processing (SP) landscape has been enriched by recent advances in artificial intelligence (AI) and machine learning (ML), yielding new tools for signal estimation, classification, prediction, and manipulation. Layered signal representations, nonlinear function approximation and nonlinear signal prediction are now feasible at very large scale in both dimensionality and data size. These are leading to significant performance gains in a variety of long-standing problem domains like speech and Image analysis. As well as providing the ability to construct new classes of nonlinear functions (e.g., fusion, nonlinear filtering).This book will help academics, researchers, developers, graduate and undergraduate students to comprehend complex SP data across a wide range of topical application areas such as social multimedia data collected from social media networks, medical imaging data, data from Covid tests etc. This book focuses on AI utilization in the speech, image, communications and yirtual reality domains.

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All books in our catalog are Original.
The book is written in English.
The binding of this edition is Hardcover.

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