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Information Fusion
Jinxing Li, Bob Zhang, David Zhang (Gebundene Ausgabe, Englisch)
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Beschreibung
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. Dieses Produkt haben wir gerade leider nicht auf Lager.
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Bis zu 50 % günstiger als neu
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Technische Daten
Erscheinungsdatum
04.05.2022
Sprache
Englisch
EAN
9789811689758
Herausgeber
Springer Singapore
Sonderedition
Nein
Autor
Jinxing Li, Bob Zhang, David Zhang
Seitenanzahl
260
Auflage
1
Einbandart
Gebundene Ausgabe
Buch Untertitel
Machine Learning Methods
Schlagwörter
Information Fusion, Data Fusion, Multi-view data, Multi-modal data, Multi-feature data, Multi-view Learning, Collaborative Representation, Sparse Representation, Weight Fusion, Classifier Fusion, Kernel, Metric Learning, Deep Learning
Thema-Inhalt
UYT - Bildverarbeitung
UYQ - Künstliche Intelligenz
UNF - Data Mining
UYQE - Wissensbasierte Systeme, Expertensysteme
Höhe
235 mm
Breite
15.5 cm
Hersteller: Springer Nature Customer Service Center GmbH, ProductSafety@springernature.com
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