2.035 hasil untuk machine learning
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Smart Racket – Instrumented Racket as Real-time Feedback Device in Table Tennis
In modern sports, often digitalized sensor systems are applied to monitor amateur and professional athletes. Since latest advances in miniaturization of electronic components and data analysis techniques opened new possibilities in sensor design, tiny measurement devices can easily be integrated…
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Anomaliedetektion in räumlich-zeitlichen Datensätzen
…of interest and anomalies are modelled and evaluated based on different machine learning methods.
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New Insights into Bayesian Inference
This book is an introduction to the mathematical analysis of Bayesian decision-making when the state of the problem is unknown but further data about it can be obtained. The objective of such analysis is to determine the optimal decision or solution that is logically consistent with the preferences…
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Internet of Things
The term "Internet of Things" (IoT) refers to an ecosystem of interconnected physical objects and devices that are accessible through the Internet and can communicate with each other. The main strength of the IoT vision is the high impact it has created and will continue to do so on several aspects…
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4EU+ International Workshop on Recent Advancements in Artificial Intelligence
L’Intelligenza Artificiale è sempre più pervasiva in un’ampia varietà di applicazioni e nella nostra vita quotidiana: dalle applicazioni scientifiche alla produzione industriale, dalle applicazioni mediche ai sistemi biomedici, dall’intelligenza ambientale all’elettronica di consumo…
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Chapter Topological Relationship Modelling for Industrial Facility Digitisation Using Graph Neural Networks
There is rising demand for automated digital twin construction based on point cloud scans, especially in the domain of industrial facilities. Yet, current automation approaches focus almost exclusively on geometric modelling. The output of these methods is a disjoint cluster of individual elements…
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Computational Optimization Techniques and Applications
Computational optimization is an active and important area of study, practice, and research today. It covers a wide range of applications in engineering, science, and industry. It provides solutions to a variety of real-life problems in the fields of health, business, government, military…
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E-Business
This book provides the latest viewpoints of scientific research in the field of e-business. It is organized into three sections: “Higher Education and Digital Economy Development”, “Artificial Intelligence in E-Business”, and “Business Intelligence Applications”. Chapters focus on China’s higher…
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Moving Broadband Mobile Communications Forward
…as fog computing, cloud computing, and artificial intelligence (AI) and machine learning (ML). It also presents use cases showing practical aspects from 5G deployment scenarios, where other communications technologies will co-habit to build the landscape of next-generation mobile networks (NGMNs).
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Pervasive Computing in IoT
In the era of Internet of Things (IoT) that we have entered, the “Monitoring–Decision–Execution” cycle of typical autonomic and automation systems is extended to include distributed developments that might scale from a smart home or greenhouse to a smart city, and from autonomous driving to…
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The Convergence of Human and Artificial Intelligence on Clinical Care - Part I
…the density of clinical data for improving downstream modeling; (ii) machine-learning-empowered diagnosis models; (iii) machine learning models for outcome prediction; (iv) innovative use of AI to improve our understanding of the public view; and (v) understanding of the attitude of providers in…
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Industry 4.0
This book presents an overview of Industry 4.0 (IR4.0) technologies including the Internet of Things (IoT), big data, data mining, deep learning, machine learning, Artificial Intelligence (AI), and cloud/edge computing. It also provides detailed insight into the impact of cutting-edge technologies…
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Graph Theory
This book is prepared as a combination of the manuscripts submitted by respected mathematicians and scientists around the world. As an editor, I truly enjoyed reading each manuscript. Not only will the methods and explanations help you to understand more about graph theory, but I also hope you will…
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Updates in Volcanology
Updates in Volcanology - Transdisciplinary Nature of Volcano Science is a true reflection of the recent advancement of volcano science to a geosystem science based on a strong source-to-surface or process-to-consequences nature, all centered around the transdisciplinary nature of volcanology. The…
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Mediterranean Identities
What is the Mediterranean? The perception of the Mediterranean leans equally on the nature, culture, history, lifestyle, and landscape. To approach the question of identity, it seems that we have to give importance to all of these. There is no Mediterranean identity, but Mediterranean identities…
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Deep material networks for efficient scale-bridging in thermomechanical simulations of solids
We investigate deep material networks (DMN). We lay the mathematical foundation of DMNs and present a novel DMN formulation, which is characterized by a reduced number of degrees of freedom. We present a efficient solution technique for nonlinear DMNs to accelerate complex two-scale simulations…
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AI and Financial Markets
Artificial intelligence (AI) is regarded as the science and technology for producing an intelligent machine, particularly, an intelligent computer program. Machine learning is an approach to realizing AI comprising a collection of statistical algorithms, of which deep learning is one such example…
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AI in Medical Imaging and Image Processing
This compilation emphasizes the transformative role of artificial intelligence (AI) and machine learning (ML) in the healthcare field, illustrating their potential to refine diagnostics, treatment protocols, and patient management. The studies confront critical healthcare challenges, presenting…
Juga tersedia di: DOAB
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Methoden des bestärkenden Lernens für die Produktionsablaufplanung
In diesem Open-Access-Buch wird eine Methode zur Adaption, Integration und Anwendung von bestärkenden Lernverfahren (Reinforcement Learning) für die Produktionsablaufplanung beschrieben. Die Methode wird anhand von typischen Problemstellungen der Produktionsablaufplanung hergeleitet und evaluiert…
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