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Více informací o knize Robust Recognition via Information Theoretic Learning

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Anotace knihy

This SpringerBrief 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.

Parametry knihy

Zařazení knihy Knihy v angličtině Computing & information technology Computer science Artificial intelligence

• Plný název: Robust Recognition via Information Theoretic Learning
• Autor: Ran He, Baogang Hu, Xiaotong Yuan, Liang Wang
• Jazyk: Angličtina
• Vazba: Brožovaná
• Počet stran: 110
• EAN: 9783319074153
• ISBN: 3319074156
• ID: 02723651
• Nakladatelství: Springer International Publishing AG
• Hmotnost: 203 g
• Rozměry: 235 × 155 × 8 mm
• Datum vydání: 29. August 2014

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