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Deep learners and deep learner descr...

Nanni, Loris.

Deep learners and deep learner descriptors for medical applications

Record Type:	Electronic resources : Monograph/item
Title/Author:	Deep learners and deep learner descriptors for medical applicationsedited by Loris Nanni ... [et al.].
other author:	Nanni, Loris.
Published:	Cham :Springer International Publishing :2020.
Description:	xi, 284 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Machine learning.
Online resource:	https://doi.org/10.1007/978-3-030-42750-4
ISBN:	9783030427504$q(electronic bk.)

Deep learners and deep learner descriptors for medical applications
Deep learners and deep learner descriptors for medical applications[electronic resource] /edited by Loris Nanni ... [et al.]. - Cham :Springer International Publishing :2020. - xi, 284 p. :ill., digital ;24 cm. - Intelligent systems reference library,v.1861868-4394 ;. - Intelligent systems reference library ;v.24..

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.

ISBN: 9783030427504$q(electronic bk.)

Standard No.: 10.1007/978-3-030-42750-4doiSubjects--Topical Terms:

188639
Machine learning.

LC Class. No.: Q325.5 / .D447 2020

Dewey Class. No.: 006.31

Deep learners and deep learner descriptors for medical applications
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520 $a 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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