Learning to learn in medical applications: A journey through optimization
Farshad A, Yeganeh Y, Navab N (2022)
Publication Type: Authored book
Publication year: 2022
Publisher: Elsevier
ISBN: 9780323998512
DOI: 10.1016/B978-0-32-399851-2.00008-9
Abstract
Meta learning or learning to learn has been an attractive topic of research in the past years. Different methods in this area have been proposed to solve existing problems in the machine learning world. One of the common problems in machine learning that has received much attention in recent years is few-shot learning. Meta learning has been the natural solution to many few-shot learning problems. In this chapter, we introduce some background in meta learning. Then, we provide some examples of its applications in different areas, especially in medical imaging.
Involved external institutions
Germany (DE)How to cite
APA:
Farshad, A., Yeganeh, Y., & Navab, N. (2022). Learning to learn in medical applications: A journey through optimization. Elsevier.
MLA:
Farshad, Azade, Yousef Yeganeh, and Nassir Navab. Learning to learn in medical applications: A journey through optimization. Elsevier, 2022.
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