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02899nam a22005175i 4500 |
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978-3-319-07416-0 |
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DE-He213 |
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20151204190124.0 |
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140828s2014 gw | s |||| 0|eng d |
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|a 9783319074160
|9 978-3-319-07416-0
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|a 10.1007/978-3-319-07416-0
|2 doi
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|d GrThAP
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|a T385
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|a TA1637-1638
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|a TK7882.P3
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|a UYQV
|2 bicssc
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|a COM016000
|2 bisacsh
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|a 006.6
|2 23
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|a He, Ran.
|e author.
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|a Robust Recognition via Information Theoretic Learning
|h [electronic resource] /
|c by Ran He, Baogang Hu, Xiaotong Yuan, Liang Wang.
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|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2014.
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|a XI, 110 p. 29 illus., 25 illus. in color.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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|a text file
|b PDF
|2 rda
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|a SpringerBriefs in Computer Science,
|x 2191-5768
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|a Introduction -- M-estimators and Half-quadratic Minimization -- Information Measures -- Correntropy and Linear Representation -- ℓ1 Regularized Correntropy -- Correntropy with Nonnegative Constraint.
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|a 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. The authors resort to a new information theoretic concept, correntropy, as a robust measure and apply it to solve robust face recognition and object recognition problems. For computational efficiency, the brief introduces the additive and multiplicative forms of half-quadratic optimization to efficiently minimize entropy problems and a two-stage sparse presentation framework for large scale recognition problems. It also describes the strengths and deficiencies of different robust measures in solving robust recognition problems.
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650 |
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|a Computer science.
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|a Computer graphics.
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|a Image processing.
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|a Computer Science.
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|a Computer Imaging, Vision, Pattern Recognition and Graphics.
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650 |
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|a Image Processing and Computer Vision.
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700 |
1 |
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|a Hu, Baogang.
|e author.
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1 |
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|a Yuan, Xiaotong.
|e author.
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1 |
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|a Wang, Liang.
|e author.
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2 |
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|a SpringerLink (Online service)
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|t Springer eBooks
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776 |
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|i Printed edition:
|z 9783319074153
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830 |
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|a SpringerBriefs in Computer Science,
|x 2191-5768
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856 |
4 |
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|u http://dx.doi.org/10.1007/978-3-319-07416-0
|z Full Text via HEAL-Link
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912 |
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|a ZDB-2-SCS
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950 |
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|a Computer Science (Springer-11645)
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