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ECCV
2010
Springer
9 years 1 months ago
Improving the Fisher Kernel for Large-Scale Image Classification
Abstract. The Fisher kernel (FK) is a generic framework which combines the benefits of generative and discriminative approaches. In the context of image classification the FK was s...
CVPR
2010
IEEE
9 years 1 months ago
Large-Scale Image Retrieval with Compressed Fisher Vectors
The problem of large-scale image search has been traditionally addressed with the bag-of-visual-words (BOV). In this article, we propose to use as an alternative the Fisher kernel...
Florent Perronnin, Yan Liu, Jorge Sanchez, Herve P...
TNN
2008
182views more  TNN 2008»
8 years 11 months ago
Large-Scale Maximum Margin Discriminant Analysis Using Core Vector Machines
Abstract--Large-margin methods, such as support vector machines (SVMs), have been very successful in classification problems. Recently, maximum margin discriminant analysis (MMDA) ...
Ivor Wai-Hung Tsang, András Kocsor, James T...
CVPR
2010
IEEE
9 years 2 months ago
Large-Scale Image Categorization with Explicit Data Embedding
Kernel machines rely on an implicit mapping of the data such that non-linear classification in the original space corresponds to linear classification in the new space. As kernel ...
Florent Perronnin, Jorge Sanchez, Yan Liu
JMLR
2006
156views more  JMLR 2006»
8 years 11 months ago
Large Scale Multiple Kernel Learning
While classical kernel-based learning algorithms are based on a single kernel, in practice it is often desirable to use multiple kernels. Lanckriet et al. (2004) considered conic ...
Sören Sonnenburg, Gunnar Rätsch, Christi...
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