検索結果 - machine learning (algorithm OR algorithms)

  1. Security and Privacy in Networks and Multimedia

    出版事項 2024
    “…Intrusion detection and AI-enhanced security feature prominently, with the methods presented including semi-supervised alert filtering and the Improved Sine Cosine Algorithm with deep learning for anomaly detection. …”
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  2. Digital Image Processing: Advanced Technologies and Applications

    出版事項 2024
    “…Covering a wide range of topics, the following Special Issue includes contributions on advanced image analysis techniques, machine learning algorithms for object detection, real-time image processing systems, and innovative solutions for complex imaging challenges. …”
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  3. Formal Methods

    出版事項 2024
    主題: “…machine learning…”
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  4. Formal Methods

    出版事項 2024
    主題: “…machine learning…”
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    Online
  5. Foundations of Robotics

    出版事項 2024
    “…The book provides an inspired, up-to-date and multidisciplinary introduction to robotics in its many forms, including emerging topics related to robotics on Machine Learning, ethics, Human-Robot Interaction, and Design Thinking. …”
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  6. Recent Topics in Highway Engineering

    出版事項 2024
    “…The latest techniques for traffic evaluation and road safety are also presented, such as the evaluation of loopholes, the optimization of fast lanes and lane-keeping systems, and the use of machine learning algorithms. This book helps readers maximize the effectiveness of different aspects of highway engineering. …”
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  7. Plato and the Nerd 著者: Lee, Edward Ashford

    出版事項 2024
    主題: “…machine learning…”
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  8. The Coevolution 著者: Lee, Edward Ashford

    出版事項 2024
    主題: “…thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning…”
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  9. Beyond the Creative Species 著者: Bown, Oliver

    出版事項 2024
    “…Drawing on a wide range of disciplines, including artificial intelligence and machine learning, design, social theory, the psychology of creativity, and creative practice research, Bown argues that to understand computational creativity, we must not only consider what computationally creative algorithms actually do, but also examine creative artistic activity itself.After describing the state of the art in computational creativity—including past and present cycles of hype—Bown examines the psychology of creativity and how it may be amenable to algorithmic automation. …”
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