9789819572052 - smartphone sensor-based human activity recognition system: in-depth design analysis with new tools and techniques (transactions on computer systems and networks) de choudhury, nurul amin; soni, badal (10 resultados)
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Hardcover. Condición: new. Hardcover. This book provides an in-depth analysis of the design and implementation of a smartphone sensor-based Human Activity Recognition (HAR) system using advanced learning models. It offers detailed insights into key advancements and future directions for HAR system development. The content includ…es a comprehensive literature review on wearable sensor-based HAR, along with descriptions of publicly available datasets for building HAR systems. To overcome the limitations of existing sensor-based HAR systems, the book emphasizes the creation of a robust HAR dataset in uncontrolled environments. This dataset is developed using built-in smartphone sensors, enabling real-time activity classification. The book presents multiple effective and optimized classifiers for developing efficient HAR systems, leveraging both self-generated and publicly available data.The book demonstrates high effectiveness in real-time activity classification and addresses common challenges such as class imbalance and domain shift. It provides practical methodologies and techniques to enhance HAR system performance. This book is an essential resource for professionals, healthcare practitioners, academics, researchers, and students specializing in health applications, signal processing, machine learning, ensemble learning, and deep learning. It offers extensive analysis and actionable insights for investigators, helping streamline product development through intelligent learning algorithms in the field of Human Activity Recognition. This book provides an in-depth analysis of the design and implementation of a smartphone sensor-based Human Activity Recognition (HAR) system using advanced learning models. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides an in-depth analysis of the design and implementation of a smartphone sensor-based Human Activity Recognition (HAR) system using advanced learning models. It offers detailed insights into key advancements and future directions for HAR s…ystem development. The content includes a comprehensive literature review on wearable sensor-based HAR, along with descriptions of publicly available datasets for building HAR systems. To overcome the limitations of existing sensor-based HAR systems, the book emphasizes the creation of a robust HAR dataset in uncontrolled environments. This dataset is developed using built-in smartphone sensors, enabling real-time activity classification. The book presents multiple effective and optimized classifiers for developing efficient HAR systems, leveraging both self-generated and publicly available data.The book demonstrates high effectiveness in real-time activity classification and addresses common challenges such as class imbalance and domain shift. It provides practical methodologies and techniques to enhance HAR system performance. This book is an essential resource for professionals, healthcare practitioners, academics, researchers, and students specializing in health applications, signal processing, machine learning, ensemble learning, and deep learning. It offers extensive analysis and actionable insights for investigators, helping streamline product development through intelligent learning algorithms in the field of Human Activity Recognition.
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Hardcover. Condición: Brand New. 116 pages. 6.30x0.51x9.49 inches. In Stock.
Idioma: Inglés
Editorial: Springer, Berlin, Springer Nature Singapore Mai 2026, 2026
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides an in-depth analysis of the design and implementation of a smartphone sensor-based Human Activity Recognition (HAR) system using advanced learning models. It offers detailed insights into key advancements and future dire…ctions for HAR system development. The content includes a comprehensive literature review on wearable sensor-based HAR, along with descriptions of publicly available datasets for building HAR systems. To overcome the limitations of existing sensor-based HAR systems, the book emphasizes the creation of a robust HAR dataset in uncontrolled environments. This dataset is developed using built-in smartphone sensors, enabling real-time activity classification. The book presents multiple effective and optimized classifiers for developing efficient HAR systems, leveraging both self-generated and publicly available data.The book demonstrates high effectiveness in real-time activity classification and addresses common challenges such as class imbalance and domain shift. It provides practical methodologies and techniques to enhance HAR system performance. This book is an essential resource for professionals, healthcare practitioners, academics, researchers, and students specializing in health applications, signal processing, machine learning, ensemble learning, and deep learning. It offers extensive analysis and actionable insights for investigators, helping streamline product development through intelligent learning algorithms in the field of Human Activity Recognition. 101 pp. Englisch.
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Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.
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Buch. Condición: Neu. Smartphone Sensor-Based Human Activity Recognition System | In-Depth Design Analysis with New Tools and Techniques | Nurul Amin Choudhury (u. a.) | Buch | Transactions on Computer Systems and Networks | xv | Englisch | 2026 | Springer | EAN 9789819572052 | Verantwortliche Person für die EU: Springer Verlag…GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.
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Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book provides an in-depth analysis of the design and implementation of a smartphone sensor-based Human Activity Recognition (HAR) system using advanced learning models. It offers detailed insights into key advancements and future directio…ns for HAR system development. The content includes a comprehensive literature review on wearable sensor-based HAR, along with descriptions of publicly available datasets for building HAR systems. To overcome the limitations of existing sensor-based HAR systems, the book emphasizes the creation of a robust HAR dataset in uncontrolled environments. This dataset is developed using built-in smartphone sensors, enabling real-time activity classification. The book presents multiple effective and optimized classifiers for developing efficient HAR systems, leveraging both self-generated and publicly available data. The book demonstrates high effectiveness in real-time activity classification and addresses common challenges such as class imbalance and domain shift. It provides practical methodologies and techniques to enhance HAR system performance. This book is an essential resource for professionals, healthcare practitioners, academics, researchers, and students specializing in health applications, signal processing, machine learning, ensemble learning, and deep learning. It offers extensive analysis and actionable insights for investigators, helping streamline product development through intelligent learning algorithms in the field of Human Activity Recognition.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 120 pp. Englisch.
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Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books
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Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios
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