Artificial Intelligence and Internet of Things Based Augmented Trends for Data Driven Systems
- 2-4 uger.
- 28. december 2024
På lager
Forlænget returret til d. 31. januar 2025
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- Adgang til 70.000+ titler
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Ingen binding og kan opsiges når som helst.
- 1 valgfrit digitalt ugeblad
- 20 timers lytning og læsning
- Adgang til 70.000+ titler
- Ingen binding
Abonnementet koster 75 kr./md.
Ingen binding og kan opsiges når som helst.
Beskrivelse af Artificial Intelligence and Internet of Things Based Augmented Trends for Data Driven Systems
This book comprehensively discusses the role of cloud computing in artificial intelligence-based data-driven systems, and hybrid cloud computing for large data-driven applications. It further explores new approaches, paradigms, and frameworks to meet societal challenges by providing solutions for critical insights into data. The text provides internet of things-based frameworks and advanced computing techniques to deal with online/virtual systems.
This book:
- Covers aspects of security, authentication, and prediction for data-driven systems in heterogeneous environments.
- Provide data-driven frameworks in combination with the internet of things, artificial intelligence, and computing to provide critical insights and decision-making for real-time problems.
- Showcases deep learning-based computer vision algorithms for enhanced pattern detection in different domains based on data-centric approaches.
- Examines the role of the internet of things and machine learning algorithms for data-driven systems.
- Highlights the applications of data-driven systems and cloud computing in enhancing network performance.
This book is primarily written for senior undergraduate, graduate students, and academic researchers in diverse fields including electrical engineering, electronics and communications engineering, computer science, and engineering.
This book:
- Covers aspects of security, authentication, and prediction for data-driven systems in heterogeneous environments.
- Provide data-driven frameworks in combination with the internet of things, artificial intelligence, and computing to provide critical insights and decision-making for real-time problems.
- Showcases deep learning-based computer vision algorithms for enhanced pattern detection in different domains based on data-centric approaches.
- Examines the role of the internet of things and machine learning algorithms for data-driven systems.
- Highlights the applications of data-driven systems and cloud computing in enhancing network performance.
This book is primarily written for senior undergraduate, graduate students, and academic researchers in diverse fields including electrical engineering, electronics and communications engineering, computer science, and engineering.
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