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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 231,66
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 235,08
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Añadir al carritoCondición: As New. Unread book in perfect condition.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
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Añadir al carritoCondición: As New. Unread book in perfect condition.
Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
EUR 272,98
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Añadir al carritoPAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.
Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de America
EUR 279,48
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Añadir al carritoPAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 279,44
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 279,43
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 299,62
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 305,79
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 305,60
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Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
EUR 358,59
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Añadir al carritoHRD. Condición: New. New Book. Shipped from UK. Established seller since 2000.
Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de America
EUR 366,98
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Añadir al carritoHRD. Condición: New. New Book. Shipped from UK. Established seller since 2000.
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 278,10
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Meta-learning, or learning to learn, has been gaining popularity in recent years to adapt to new tasks systematically and efficiently in machine learning. In the book, Meta-Learning Frameworks for Imaging Applications , experts from the fields of machine learning and imaging come together to explore the current state of meta-learning and its application to medical imaging and health informatics. The book presents an overview of the meta-learning framework, including common versions such as model-agnostic learning, memory augmentation, prototype networks, and learning to optimize. It also discusses how meta-learning can be applied to address fundamental limitations of deep neural networks, such as high data demand, computationally expensive training, and limited ability for task transfer. One critical topic in imaging is image segmentation, and the book explores how a meta-learning-based framework can help identify the best image segmentation algorithm, which would be particularly beneficial in the healthcare domain. This book is relevant to healthcare institutes, e-commerce companies, and educational institutions, as well as professionals and practitioners in the intelligent system, computational data science, network applications, and biomedical applications fields. It is also useful for domain developers and project managers from diagnostic and pharmacy companies involved in the development of medical expert systems. Additionally, graduate and master students in intelligent systems, big data management, computational intelligent approaches, computer vision, and biomedical science can use this book for their final projects and specific courses.
Publicado por Engineering Science Reference, 2023
ISBN 10: 1668476606 ISBN 13: 9781668476604
Idioma: Inglés
Librería: Revaluation Books, Exeter, Reino Unido
EUR 311,93
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Añadir al carritoPaperback. Condición: Brand New. 300 pages. 10.00x7.00x0.58 inches. In Stock. This item is printed on demand.
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 359,37
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Añadir al carritoBuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Meta-learning, or learning to learn, has been gaining popularity in recent years to adapt to new tasks systematically and efficiently in machine learning. In the book, Meta-Learning Frameworks for Imaging Applications , experts from the fields of machine learning and imaging come together to explore the current state of meta-learning and its application to medical imaging and health informatics. The book presents an overview of the meta-learning framework, including common versions such as model-agnostic learning, memory augmentation, prototype networks, and learning to optimize. It also discusses how meta-learning can be applied to address fundamental limitations of deep neural networks, such as high data demand, computationally expensive training, and limited ability for task transfer. One critical topic in imaging is image segmentation, and the book explores how a meta-learning-based framework can help identify the best image segmentation algorithm, which would be particularly beneficial in the healthcare domain. This book is relevant to healthcare institutes, e-commerce companies, and educational institutions, as well as professionals and practitioners in the intelligent system, computational data science, network applications, and biomedical applications fields. It is also useful for domain developers and project managers from diagnostic and pharmacy companies involved in the development of medical expert systems. Additionally, graduate and master students in intelligent systems, big data management, computational intelligent approaches, computer vision, and biomedical science can use this book for their final projects and specific courses.
Publicado por Engineering Science Reference, 2023
ISBN 10: 1668476592 ISBN 13: 9781668476598
Idioma: Inglés
Librería: Revaluation Books, Exeter, Reino Unido
EUR 411,59
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Añadir al carritoHardcover. Condición: Brand New. 300 pages. 10.00x7.00x0.69 inches. In Stock. This item is printed on demand.