2.035 hasil untuk machine learning
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Algorithms for Games AI
…planning and searching to modern algorithms such as deep reinforcement learning. The papers in this Special Issue address both the theoretical and practical challenges of the application of these algorithms. This reprint presents eleven papers covering a wide range of game AI topics, including the…
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Learning Ontology Relations by Combining Corpus-Based Techniques and Reasoning on Data from Semantic Web Sources
The manual construction of formal domain conceptualizations (ontologies) is labor-intensive. Ontology learning, by contrast, provides (semi-)automatic ontology generation from input data such as domain text. This thesis proposes a novel approach for learning labels of non-taxonomic ontology…
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Pattern Recognition
…students, researchers, and practicing engineers working in the field of machine vision and computer science and engineering.
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Zastosowanie uczenia maszynowego do obrazowania stanu zawilgocenia murów z wykorzystaniem tomografii impedancyjnej
…building walls. Both deterministic methods and modern methods based on machine learning were used in the research. The research was conducted in laboratory conditions and in the historical building of the Golden Gate in Gdańsk. A hybrid, multi-branch neural network model was developed, which was…
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Proceedings of the Second International Forum on Financial Mathematics and Financial Technology
…mathematical models and state-of-the-art technologies such as deep learning, with the aim to improve the financial analysis and decision-making and enhance the quality of financial services and risk control. The variety of the papers delivers added value for both scholars and practitioners where…
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Classification Handbook for Beginners
Artificial intelligence and machine learning have become indispensable pillars of today's rapidly evolving technological landscape. At the heart of these advancements lie classification algorithms, key tools in the data science domain. From diagnosing diseases to analyzing customer behavior, and…
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Shaping the Future of IoT with Edge Intelligence
…applications. The second part presents IoT applications that employ machine learning and other forms of Artificial Intelligence at the edge of the network. The third part illustrates decentralized IoT applications based on distributed ledger technologies. The fourth part is devoted to the…
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The Road to General Intelligence
…the range of viable automation tasks.The recent notable successes of Machine Learning has lead to conjecture that it might be the appropriate technology for delivering General Intelligence. In this book, we argue that the framework of machine learning is fundamentally at odds with any reasonable…
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Future Trends in Education Post COVID-19
…utilization in improving the quality of education, teaching and learning. It discusses the transformation of the curriculum, such as course design and delivery, assessment, and instructional methodologies that focus on employment readiness for the ever-evolving job market. Contributions include a…
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Modellfreies Lernen optimaler zeitdiskreter Regelungsstrategien für Fertigungsprozesse mit endlichem Zeithorizont
The quality and performance of components is largely determined by the execution of the manufacturing processes involved. The process result depends -- in addition to the initial state of the component and the process -- on the course of the process. In many manufacturing processes, the course of…
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Data-Driven Intelligent Modeling and Optimization Algorithms for Industrial Processes
…risk assessment, large language models, self-supervised key-point learning, trustworthy article ranking, engine optimization model, and bioinspired generative design. These powerful and intelligent algorithms use data for control, decision making, and parameter optimization, driving industrial…
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Advancement of Mathematical Methods in Feature Representation Learning for Artificial Intelligence, Data Mining and Robotics
The present reprint contains 33 articles accepted and published in the Special Issue entitled “Advancement of Mathematical Methods in Feature Representation Learning for Artificial Intelligence, Data Mining and Robotics, 2022” in the MDPI journal, Mathematics, which covers a wide range of topics…
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Superintelligence Series Volume 1: Artificial Intelligence for Operational and Predictive Optimization
…support analysis and decision-making in real settings. By combining deep learning, genetic algorithms, expert systems, and hybrid models, the studies reflect current practices rather than abstract experimentation. Attention is also given to ethical and sustainable adoption, linking technical…
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The Future of Healthcare
Biomedical technology, which is fundamental today, incorporates various disciplines such as signal, image, and data processing, greatly benefiting healthcare systems. Artificial intelligence plays a crucial role in allowing the creation of embedded systems that monitor and adjust patient treatment…
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Unlocking Artificial Intelligence
This open access book provides a state-of-the-art overview of current machine learning research and its exploitation in various application areas. It has become apparent that the deep integration of artificial intelligence (AI) methods in products and services is essential for companies to stay…
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Chapter Robotic Assembly and Reuse of Modular Elements in the Supply Chain of a Learning Factory for Construction and in the Context of Circular Economy
…providing hands-on education and research experiences, defined hereby as Learning Factory for Construction (LFC). This paper presents a scaled-down version of a LFC that has a robotic manipulator perform fully-automated and precise assembly, deconstruction, and reuse tasks of modular construction…
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Chapter Efficient Data Curation Using Active Learning for a Video-Based Fire Detection
…and expensive, making it difficult to obtain sufficient data for training machine learning models. To address this challenge, uncertainty-based active learning techniques can be used to iteratively select the most informative samples for labeling. This can reduce the amount of labeled data needed…
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Computational Methods for Medical and Cyber Security
Over the past decade, computational methods, including machine learning (ML) and deep learning (DL), have been exponentially growing in their development of solutions in various domains, especially medicine, cybersecurity, finance, and education. While these applications of machine learning…
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Recent Applications in Data Clustering
Clustering has emerged as one of the more fertile fields within data analytics, widely adopted by companies, research institutions, and educational entities as a tool to describe similar/different groups. The book Recent Applications in Data Clustering aims to provide an outlook of recent…
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