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theories Computational Intelligence and Feature Selection is an ideal resource for advanced undergraduates, postgraduates, researchers, and;
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This book constitutes the proceedings of the Second Australasian Conference on Artificial Life and Computational Intelligence, ACALCI;
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Biosignal Processing and Classification Using Computational Learning and Intelligence: Principles, Algorithms and Applications posits an;
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issues, Computational Methods of Feature Selection introduces the basic concepts and principles, state-of-the-art algorithms, and novel;
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computational complexity, abundance of pattern features, sensitivity to size and shape variations and poor performance against complex backgrounds. The;
Vergelijkbare producten zoals Computational Intelligence in Multi Feature Visual Pattern Recognition
This book discusses feature engineering and computational intelligence solutions for ECG monitoring, with a particular focus on how these;
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Foundations of Computational Intelligence Volume 5: Function Approximation and Classification Approximation theory is that area of analysis;
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face the problem of intractable computational time. Since no single feature selection method could handle all requirements of feature selection;
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This book describes how to use computational intelligence and artificial intelligence tools to improve the decision-making process in new;
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intelligent biomedical image processing and analysis. It develops computational models, methods and tools for biomedical engineering related to;
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and computational intelligence, as Supervised and Unsupervised Pattern Recognition does. This volume describes the application of a novel;
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These transactions publish research in computer-based methods of computational collective intelligence (CCI) and their applications in a;
Vergelijkbare producten zoals Transactions on Computational Collective Intelligence XXXV
and goal programming, feature selection by the binary flower pollination algorithm, job shop scheduling, single row facility layout;
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the cloud, recurrent neural networks, deep learning models, and feature selection and engineering Learn more about deep learning algorithms;
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by leading scientists, researchers and research scholars from around the globe on all aspects of computational intelligence. The work;
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This book constitutes the proceedings of the Second International Conference on Mining Intelligence and Knowledge Exploration, MIKE 2014;
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Computational Intelligence Techniques and Their Applications to Software Engineering Problems focuses on computational intelligence;
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Multidisciplinary Computational Intelligence Techniques: Applications in Business, Engineering, and Medicine explores the complex world;
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compression, data clustering, and feature selection. The content will be valuable for researchers and postgraduate students in computer science;
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submissions. They are organized in topical sections such as multi-agent systems; social networks and NLP; sentiment analysis; computational;
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submissions. They are organized in topical sections such as multi-agent systems; social networks and NLP; sentiment analysis; computational;
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Take the next step in Integrated Product and Process Development This pioneering book is the first to apply state-of-the-art computational;
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existing feature selection algorithms and developing new algorithms for emerging problems in real-world applications. This technique represents a;
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existing feature selection algorithms and developing new algorithms for emerging problems in real-world applications. This technique represents a;
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Image Processing: A Computational Intelligence Perspective provides an authoritative and detailed account of computational intelligence (CI;
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intelligence, fuzzy sets and vague sets, rough set theoretic approaches, quantum-inspired computational intelligence, hybrid computational intelligence;
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The field of computational intelligence has grown tremendously over that past five years, thanks to evolving soft computing and;
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