Robust Recognition via Information Theoretic Learning
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 e…
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Produktdetails
Weitere Autoren: Wang, Liang / He, Ran / Hu, Baogang
- ISBN: 978-3-319-07416-0
- EAN: 9783319074160
- Produktnummer: 17330502
- Verlag: Springer
- Sprache: Englisch
- Erscheinungsjahr: 2014
- Plattform: PDF
- Masse: 2'878 KB
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