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Meta Learning With Medical Imaging and Health Informatics Applications

Edited by Hien Van Nguyen, Edited by Ronald Summers, Edited by Rama Chellappa

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normal price: R 4 054.95

Price: R 3 851.95


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Meta-Learning, or learning to learn, has become increasingly popular in recent years. Instead of building AI systems from scratch for each machine learning task, Meta-Learning constructs computational mechanisms to systematically and efficiently adapt to new tasks. The meta-learning paradigm has great potential to address deep neural networks’ fundamental challenges such as intensive data requirement, computationally expensive training, and limited capacity for transfer among tasks. This book provides a concise summary of Meta-Learning theories and their diverse applications in medical imaging and health informatics. It covers the unifying theory of meta-learning and its popular variants such as model-agnostic learning, memory augmentation, prototypical networks, and learning to optimize. The book brings together thought leaders from both machine learning and health informatics fields to discuss the current state of Meta-Learning, its relevance to medical imaging and health informatics, and future directions.

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Normally shipped | Usually dispatched in 3 to 6 weeks as supplier is out of stock
Publisher | Elsevier Science & Technology
Published date | 29 Sep 2022
Language |
Format | Paperback / softback
Pages | 428
Dimensions | 235 x 191 x 0mm (L x W x H)
Weight | 870g
ISBN | 978-0-3239-9851-2
Readership Age |
BISAC |


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Normally shipped | Available from overseas. Usually dispatched in 14 days
Readership Age |
Normal Price | R 5 589.95
Price | R 5 309.95 | on special |



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