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Advances in Machine Learning/Deep Learning-based Technologies
Details
As the 4th Industrial Revolution is restructuring human societal organization into, so-called, Society 5.0, the field of Machine Learning (and its sub-field of Deep Learning) and related technologies is growing continuously and rapidly, developing in both itself and towards applications in many other disciplines. Researchers worldwide aim at incorporating cognitive abilities into machines, such as learning and problem solving. When machines and software systems have been enhanced with Machine Learning/Deep Learning components, they become better and more efficient at performing specific tasks. Consequently, Machine Learning/Deep Learning stands out as a research discipline due to its worldwide pace of growth in both theoretical advances and areas of application, while achieving very high rates of success and promising major impact in science, technology and society.
The book at hand aims at exposing its readers to some of the most significant Advances in Machine Learning/Deep Learning-based Technologies. The book consists of an editorial note and an additional ten (10) chapters, all invited from authors who work on the corresponding chapter theme and are recognized for their significant research contributions. In more detail, the chapters in the book are organized into five parts, namely (i) Machine Learning/Deep Learning in Socializing and Entertainment, (ii) Machine Learning/Deep Learning in Education, (iii) Machine Learning/Deep Learning in Security, (iv) Machine Learning/Deep Learning in Time Series Forecasting, and (v) Machine Learning in Video Coding and Information Extraction .
This research book is directed towards professors, researchers, scientists, engineers and students in Machine Learning/Deep Learning-related disciplines. It is also directed towards readers who come from other disciplines and are interested in becoming versed in some of themost recent Machine Learning/Deep Learning-based technologies. An extensive list of bibliographic references at the end of each chapter guides the readers to probe further into the application areas of interest to them.
Presents recent research on Machine Learning/Deep Learning-based Technologies, Presents Selected Papers in Honour of Professor Nikolaos G. Bourbakis Vol. 2 Written by experts in the field
Inhalt
Part I: Machine Learning/Deep Learning in Socializing and Entertainment.- Part II: Machine Learning/Deep Learning in.- Part III: Machine Learning/Deep Learning in Security.- Part IV: Machine Learning/Deep Learning in Time Series Forecasting.- Part V: Machine Learning in Video Coding and Information Extraction.
Weitere Informationen
- Allgemeine Informationen
- GTIN 09783030767969
- Genre Technology Encyclopedias
- Auflage 1st edition 2022
- Editor George A. Tsihrintzis, Lakhmi C. Jain, Maria Virvou
- Lesemotiv Verstehen
- Anzahl Seiten 248
- Herausgeber Springer International Publishing
- Größe H235mm x B155mm x T14mm
- Jahr 2022
- EAN 9783030767969
- Format Kartonierter Einband
- ISBN 3030767965
- Veröffentlichung 08.08.2022
- Titel Advances in Machine Learning/Deep Learning-based Technologies
- Untertitel Selected Papers in Honour of Professor Nikolaos G. Bourbakis - Vol. 2
- Gewicht 382g
- Sprache Englisch