"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 ex...

Ausführliche Beschreibung

Bibliographische Detailangaben

Weitere Verfasser:	Singh, Parveen 1976- (HerausgeberIn), Sengar, Sandeep 1985- (HerausgeberIn), Sharma, Ashok 1977- (HerausgeberIn)
Format:	Elektronisch E-Book
Sprache:	English
Veröffentlicht:	Hershey, Pennsylvania IGI Global 2023
Schlagworte:	Diagnostic imaging Machine learning Deep learning (Machine learning)
Online-Zugang:	DE-91 DE-898 Volltext
Zusammenfassung:	"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."
Beschreibung:	1 Online-Ressource (253 Seiten)
ISBN:	9781668476611
DOI:	10.4018/978-1-6684-7659-8