Librería: Majestic Books, Hounslow, Reino Unido
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Librería: Books Puddle, New York, NY, Estados Unidos de America
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Idioma: Inglés
Publicado por Elsevier Science Publishing Co Inc, 2026
ISBN 10: 0443330824 ISBN 13: 9780443330827
Librería: THE SAINT BOOKSTORE, Southport, Reino Unido
EUR 173,03
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Añadir al carritoPaperback / softback. Condición: New. New copy - Usually dispatched within 4 working days.
Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 175,37
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 193,14
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 187,00
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 212,63
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
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Librería: moluna, Greven, Alemania
EUR 196,21
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Añadir al carritoCondición: New. Investigates opportunities and challenges of deep learning, including convolutional neural networks (CNNs) and their applications in medical image processingIncludes comprehensive examination and elucidation of Kronecker convolutional proce.
Librería: Revaluation Books, Exeter, Reino Unido
EUR 269,20
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Añadir al carritoPaperback. Condición: Brand New. 300 pages. 9.25x7.50x10.87 inches. In Stock.
Idioma: Inglés
Publicado por Elsevier Science Publishing Co Inc Jan 2026, 2026
ISBN 10: 0443330824 ISBN 13: 9780443330827
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 274,25
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Añadir al carritoTaschenbuch. Condición: Neu. Neuware - Cutting-edge Computational Intelligence in Healthcare with Convolution and Kronecker Convolution-based Approaches focuses on the use of deep learning techniques in the field of medical imagine analysis. These advances offer promising progress in healthcare through improvements in diagnostic accuracy, efficiency in medical image interpretation, and breakthroughs in treatment planning. Divided into five sections, the book begins with foundational coverage of deep learning in medical imaging and fundamentals of Convolutional Neural Networks. Discover the role convolutions play in extracting meaningful features from images, aiding tasks such as diagnosis and segmentation. The second section takes a deep dive into Kronecker convolutions and their unique advantages, such as enhanced spatial hierarchy understanding, efficient parameter utilization, and improved adaptability to specific characteristics of medical images. Section three reviews specific applications in tumor detection, enhancing organ segmentation as well as disease classification, and section four explores real-world implementation of AI-driven diagnostic imaging, precision medicine via imaging analytics, and wearable devices and continuous health monitoring. The final section offers discussion on the unique challenges, trends, and potential future directions these innovative computational approaches have on medical image processing and advanced healthcare. In summary, this book takes an interdisciplinary approach to bridge the gap between theory and practice, fusing knowledge from the domains of medicine, computer science, and machine learning to address issues in healthcare through sophisticated image analysis techniques.
Librería: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 141,10
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Idioma: Inglés
Publicado por Elsevier Science Publishing Co Inc, San Diego, 2026
ISBN 10: 0443330824 ISBN 13: 9780443330827
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
EUR 153,84
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Añadir al carritoPaperback. Condición: new. Paperback. Cutting-edge Computational Intelligence in Healthcare with Convolution and Kronecker Convolution-based Approaches focuses on the use of deep learning techniques in the field of medical imagine analysis. These advances offer promising progress in healthcare through improvements in diagnostic accuracy, efficiency in medical image interpretation, and breakthroughs in treatment planning. Divided into five sections, the book begins with foundational coverage of deep learning in medical imaging and fundamentals of Convolutional Neural Networks. Discover the role convolutions play in extracting meaningful features from images, aiding tasks such as diagnosis and segmentation. The second section takes a deep dive into Kronecker convolutions and their unique advantages, such as enhanced spatial hierarchy understanding, efficient parameter utilization, and improved adaptability to specific characteristics of medical images. Section three reviews specific applications in tumor detection, enhancing organ segmentation as well as disease classification, and section four explores real-world implementation of AI-driven diagnostic imaging, precision medicine via imaging analytics, and wearable devices and continuous health monitoring. The final section offers discussion on the unique challenges, trends, and potential future directions these innovative computational approaches have on medical image processing and advanced healthcare. In summary, this book takes an interdisciplinary approach to bridge the gap between theory and practice, fusing knowledge from the domains of medicine, computer science, and machine learning to address issues in healthcare through sophisticated image analysis techniques. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Librería: Revaluation Books, Exeter, Reino Unido
EUR 153,64
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Añadir al carritoPaperback. Condición: Brand New. 300 pages. 9.25x7.50x10.87 inches. In Stock. This item is printed on demand.
Idioma: Inglés
Publicado por Elsevier Science Publishing Co Inc, San Diego, 2026
ISBN 10: 0443330824 ISBN 13: 9780443330827
Librería: CitiRetail, Stevenage, Reino Unido
EUR 157,55
Cantidad disponible: 1 disponibles
Añadir al carritoPaperback. Condición: new. Paperback. Cutting-edge Computational Intelligence in Healthcare with Convolution and Kronecker Convolution-based Approaches focuses on the use of deep learning techniques in the field of medical imagine analysis. These advances offer promising progress in healthcare through improvements in diagnostic accuracy, efficiency in medical image interpretation, and breakthroughs in treatment planning. Divided into five sections, the book begins with foundational coverage of deep learning in medical imaging and fundamentals of Convolutional Neural Networks. Discover the role convolutions play in extracting meaningful features from images, aiding tasks such as diagnosis and segmentation. The second section takes a deep dive into Kronecker convolutions and their unique advantages, such as enhanced spatial hierarchy understanding, efficient parameter utilization, and improved adaptability to specific characteristics of medical images. Section three reviews specific applications in tumor detection, enhancing organ segmentation as well as disease classification, and section four explores real-world implementation of AI-driven diagnostic imaging, precision medicine via imaging analytics, and wearable devices and continuous health monitoring. The final section offers discussion on the unique challenges, trends, and potential future directions these innovative computational approaches have on medical image processing and advanced healthcare. In summary, this book takes an interdisciplinary approach to bridge the gap between theory and practice, fusing knowledge from the domains of medicine, computer science, and machine learning to address issues in healthcare through sophisticated image analysis techniques. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.