Machine Learning Methods for Signal, Image and Speech Processing
Meerja Akhil Jabbar, Kantipudi MVV Prasad, Sheng-Lung Peng, Mamun Bin Ibne Reaz, Ana Maria Madureira
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 virtual reality domains.
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 virtual reality domains.
년:
2022
출판사:
River Publishers
언어:
english
페이지:
250
ISBN 10:
8770223696
ISBN 13:
9788770223690
시리즈:
River Publishers Series in Signal, Image and Speech Processing
파일:
PDF, 121.47 MB
IPFS:
,
english, 2022