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Robust Recognition via Information Theoretic Learning
Langbeschreibung
This Springer Brief represents a comprehensive review of information theoretic methods for robust recognition. A variety of information theoretic methods have been proffered in the past decade, in a large variety of computer vision applications; this work brings them together, attempts to impart the theory, optimization and usage of information entropy.
Inhaltsverzeichnis
Introduction.- M-estimators and Half-quadratic Minimization.- Information Measures.- Correntropy and Linear Representation.- l1 Regularized Correntropy.- Correntropy with Nonnegative Constraint.
ISBN-13:
9783319074160
Veröffentl:
2014
Seiten:
110
Autor:
Ran He
Serie:
SpringerBriefs in Computer Science
eBook Typ:
PDF
eBook Format:
EPUB
Kopierschutz:
1 - PDF Watermark
Sprache:
Englisch
53,49 €*
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