Meta Learning With Medical Imaging and Health Informatics Applications
Language: English
Published by Elsevier Science & Technology Sep 2022, 2022
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Add to basketItem description from seller
Neuware - 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.…
Seller Inventory # 9780323998512
- Title
- Meta Learning With Medical Imaging and Health Informatics Applications
- Author
- Ronald Summers
- Publisher
- Elsevier Science & Technology Sep 2022
- Publication year
- 2022
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 0323998518
- ISBN 13
- 9780323998512
- Item weight
- 906 grams
- Dimensions
- 236x192x27 mm
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.
- First book on applying Meta Learning to medical imaging
- Pioneers in the field as contributing authors to explain the theory and its development
- Has GitHub repository consisting of various code examples and documentation to help the audience to set up Meta-Learning algorithms for their applications quickly
"Synopsis" may belong to another edition of this title.
About the Author
Dr. Summers received a BA in physics and the M.D. and Ph.D. degrees in medicine/anatomy and cell biology from the University of Pennsylvania. He completed a medical internship at the Presbyterian-University of Pennsylvania Hospital, Philadelphia, PA, a radiology residency at the University of Michigan, Ann Arbor, MI, and an MRI fellowship at Duke University. In 2000, he received the Presidential Early Career Award for Scientists and Engineers, presented by Dr. Neal Lane, President Clinton's science advisor. In 2012, he received the NIH Director's Award, presented by NIH Director Dr. Francis S. Collins. He is an editorial board member of the journals Radiology and Academic Radiology. He was a co-chair of the Computer-aided Diagnosis program of the annual SPIE Medical Imaging conference in 2010 and 2011. He has co-authored over 300 journal, review and conference proceedings articles, and is a co-inventor on 12 patents.
Prof. Rama Chellappa received the B.E. (Hons.) degree from the University of Madras, India, in 1975 and the M.E. (Distinction) degree from Indian Institute of Science, Bangalore, in 1977. He received M.S.E.E. and Ph.D. Degrees in Electrical Engineering from Purdue University, West Lafayette, IN, in 1978 and 1981 respectively. Since 1991, he has been a Professor of Electrical Engineering and an affiliate Professor of Computer Science at University of Maryland, College Park. He is also affiliated with the Center for Automation Research (Director) and the Institute for Advanced Computer Studies (Permanent Member). In 2005, he was named a Minta Martin Professor of Engineering. Prior to joining the University of Maryland, he was an Assistant (1981-1986) and Associate Professor (1986-1991) and Director of the Signal and Image Processing Institute (1988-1990) at University of Southern California, Los Angeles.
Over the last 29 years, he has published numerous book chapters, peer-reviewed journal and conference papers. He has co-authored and edited books on MRFs, face and gait recognition and collected works on image processing and analysis. His current research interests are face and gait analysis, markerless motion capture, 3D modeling from video, image and video-based recognition and exploitation and hyper spectral processing.
"About the title" may belong to another edition of this title.
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