Information fusion: machine learning methods / Jinxing Li, Bob Zhang, David Zhang.
2022
Q325.5
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Details
Title
Information fusion: machine learning methods / Jinxing Li, Bob Zhang, David Zhang.
Author
Li, Jinxing.
ISBN
9789811689765 (electronic bk.)
9811689768 (electronic bk.)
981168975X
9789811689758
9811689768 (electronic bk.)
981168975X
9789811689758
Publication Details
Singapore : Springer, 2022.
Language
English
Description
1 online resource
Item Number
10.1007/978-981-16-8976-5 doi
Call Number
Q325.5
Dewey Decimal Classification
006.3/1
Summary
In the big data era, increasing information can be extracted from the same source object or scene. For instance, a person can be verified based on their fingerprint, palm print, or iris information, and a given image can be represented by various types of features, including its texture, color, shape, etc. These multiple types of data extracted from a single object are called multi-view, multi-modal or multi-feature data. Many works have demonstrated that the utilization of all available information at multiple abstraction levels (measurements, features, decisions) helps to obtain more complex, reliable and accurate information and to maximize performance in a range of applications. This book provides an overview of information fusion technologies, state-of-the-art techniques and their applications. It covers a variety of essential information fusion methods based on different techniques, including sparse/collaborative representation, kernel strategy, Bayesian models, metric learning, weight/classifier methods, and deep learning. The typical applications of these proposed fusion approaches are also presented, including image classification, domain adaptation, disease detection, image restoration, etc. This book will benefit all researchers, professionals and graduate students in the fields of computer vision, pattern recognition, biometrics applications, etc. Furthermore, it offers a valuable resource for interdisciplinary research.
Bibliography, etc. Note
Includes bibliographical references and index.
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Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed May 17, 2022).
Added Author
Zhang, Bob (Of Aomen da xue)
Zhang, David, 1949-
Zhang, David, 1949-
Available in Other Form
Print version: 9789811689758
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Table of Contents
Chapter 1. Introduction
Chapter 2. Information fusion based on sparse/collaborative representation
Chapter 3. Information fusion based on gaussian process latent variable model
Chapter 4. Information fusion based on multi-view and multifeature earning
Chapter 5. Information fusion based on metric learning
Chapter 6. Information fusion based on score/weight classifier fusion
Chapter 7. Information fusion based on deep learning
Chapter 8. Conclusion.
Chapter 2. Information fusion based on sparse/collaborative representation
Chapter 3. Information fusion based on gaussian process latent variable model
Chapter 4. Information fusion based on multi-view and multifeature earning
Chapter 5. Information fusion based on metric learning
Chapter 6. Information fusion based on score/weight classifier fusion
Chapter 7. Information fusion based on deep learning
Chapter 8. Conclusion.