Deep Learners and Deep Learner Descriptors for Medical Applications (eBook, PDF)

Redaktion: Nanni, Loris; Jain, Lakhmi C.; Ghidoni, Stefano; Brattin, Rick; Brahnam, Sheryl

• Format: PDF

Produktbeschreibung

This book introduces readers to the current trends in using deep learners and deep learner descriptors for medical applications. It reviews the recent literature and presents a variety of medical image and sound applications to illustrate the five major ways deep learners can be utilized: 1) by training a deep learner from scratch (chapters provide tips for handling imbalances and other problems with the medical data); 2) by implementing transfer learning from a pre-trained deep learner and extracting deep features for different CNN layers that can be fed into simpler classifiers, such as the support vector machine; 3) by fine-tuning one or more pre-trained deep learners on an unrelated dataset so that they are able to identify novel medical datasets; 4) by fusing different deep learner architectures; and 5) by combining the above methods to generate a variety of more elaborate ensembles. This book is a value resource for anyone involved in engineering deep learners for medical applications as well as to those interested in learning more about the current techniques in this exciting field. A number of chapters provide source code that can be used to investigate topics further or to kick-start new projects.

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Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 284
• Erscheinungstermin: 15. Mai 2020
• Englisch
• ISBN-13: 9783030427504
• Artikelnr.: 59460353

Inhaltsangabe

An Introduction to Deep Learners and Deep Leaner Descriptors for Medical Applications.- Feature Learning to Automatically Assess Radiographic Knee Osteoarthritis Severity.