Articoli correlati a Meta-learning Frameworks for Imaging Applications
- EditoreEngineering Science Reference
- Data di pubblicazione2023
- ISBN 10 1668476606
- ISBN 13 9781668476604
- RilegaturaCopertina flessibile
- LinguaInglese
- Numero di pagine300
- RedattoreSharma Ashok, Sengar Sandeep, Singh Parveen
Compra nuovo
Visualizza questo articolo
EUR 213,94
EUR 14,25 per la spedizione da Regno Unito a U.S.A.
Destinazione, tempi e costiAltre edizioni note dello stesso titolo
Risultati della ricerca per Meta-learning Frameworks for Imaging Applications
Foto dell'editore
Meta-Learning Frameworks for Imaging Applications
Da: Ria Christie Collections, Uxbridge, Regno Unito
Valutazione del venditore 5 su 5 stelle
Condizione: New. In. Codice articolo ria9781668476604_new
Quantità: Più di 20 disponibili
Foto dell'editore
Meta-Learning Frameworks for Imaging Applications (Paperback)
Da: CitiRetail, Stevenage, Regno Unito
Valutazione del venditore 5 su 5 stelle
Paperback. Condizione: new. Paperback. 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. "The book will bring together many experts from the domains of machine learning and imaging application to explore the current state of Meta-Learning, its application to medical imaging and health informatics, and its future directions. This book will give an overview of the Meta- Learning framework in Imaging Application"-- Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Codice articolo 9781668476604
Quantità: 1 disponibili
Foto dell'editore
Meta-Learning Frameworks for Imaging Applications
Da: PBShop.store UK, Fairford, GLOS, Regno Unito
Valutazione del venditore 4 su 5 stelle
PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000. Codice articolo GB-9781668476604
Quantità: 1 disponibili
Foto dell'editore
Meta-Learning Frameworks for Imaging Applications
Da: PBShop.store US, Wood Dale, IL, U.S.A.
Valutazione del venditore 5 su 5 stelle
PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000. Codice articolo GB-9781668476604
Quantità: 1 disponibili
Immagini fornite dal venditore
Meta-Learning Frameworks for Imaging Applications
Print on DemandDa: AHA-BUCH GmbH, Einbeck, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: 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. Codice articolo 9781668476604
Quantità: 1 disponibili
Foto dell'editore
Meta-learning Frameworks for Imaging Applications
Editore:
Engineering Science Reference, 2023
ISBN 10: 1668476606
ISBN 13: 9781668476604
Nuovo
Paperback
Da: Revaluation Books, Exeter, Regno Unito
Valutazione del venditore 5 su 5 stelle
Paperback. Condizione: Brand New. 300 pages. 10.00x7.00x0.58 inches. In Stock. This item is printed on demand. Codice articolo __1668476606
Quantità: 1 disponibili