منابع مشابه
SVDD-Based Pattern Denoising
The support vector data description (SVDD) is one of the best-known one-class support vector learning methods, in which one tries the strategy of using balls defined on the feature space in order to distinguish a set of normal data from all other possible abnormal objects. The major concern of this letter is to extend the main idea of SVDD to pattern denoising. Combining the geodesic projection...
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Illumination change is one of most important and difficult problems which prevent from applying face recognition to real applications. For solving this, we propose a method to compensate for different illumination conditions based on SVDD(Support Vector Data Description). In the proposed method, we first consider the SVDD training for the data belonging to the facial images under various illumi...
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Support vector data description (SVDD) is a well-known kernel method that constructs a minimal hypersphere regarded as a data description for a given data set. However SVDD does not take into account any statistical distribution of the data set in constructing that optimal hypersphere, and SVDD is applied to solving one-class classification problems only. This paper proposes a new approach to S...
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ژورنال
عنوان ژورنال: Neural Computation
سال: 2007
ISSN: 0899-7667,1530-888X
DOI: 10.1162/neco.2007.19.7.1919