Robust Recognition via Information Theoretic Learning is popular PDF and ePub book, written by Ran He in 2014-08-28, it is a fantastic choice for those who relish reading online the Computers genre. Let's immerse ourselves in this engaging Computers book by exploring the summary and details provided below. Remember, Robust Recognition via Information Theoretic Learning can be Read Online from any device for your convenience.
Robust Recognition via Information Theoretic Learning Book PDF Summary
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.
Detail Book of Robust Recognition via Information Theoretic Learning PDF
- Author : Ran He
- Release : 28 August 2014
- Publisher : Springer
- ISBN : 9783319074160
- Genre : Computers
- Total Page : 120 pages
- Language : English
- PDF File Size : 17,9 Mb
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