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» Separable PCA for image classification
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CVPR
2010
IEEE
15 years 7 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
ACCV
2010
Springer
14 years 11 months ago
Descriptor Learning Based on Fisher Separation Criterion for Texture Classification
Abstract. This paper proposes a novel method to deal with the representation issue in texture classification. A learning framework of image descriptor is designed based on the Fish...
Yimo Guo, Guoying Zhao, Matti Pietikäinen, Zh...
119
Voted
IJCNN
2007
IEEE
15 years 10 months ago
FEBAM: A Feature-Extracting Bidirectional Associative Memory
—In this paper, a new model that can ultimately create its own set of perceptual features is proposed. Using a bidirectional associative memory (BAM)-inspired architecture, the r...
Sylvain Chartier, Gyslain Giguère, Patrice ...
129
Voted
ICPR
2002
IEEE
16 years 5 months ago
Analyzing Non-Negative Matrix Factorization for Image Classification
The Non-negative Matrix Factorization technique (NMF) has been recently proposed for dimensionality reduction. NMF is capable to produce a region- or partbased representation of o...
Bernt Schiele, David Guillamet, Jordi Vitrià...
ACCV
2006
Springer
15 years 7 months ago
Multiple Similarities Based Kernel Subspace Learning for Image Classification
Abstract. In this paper, we propose a new method for image classification, in which matrix based kernel features are designed to capture the multiple similarities between images in...
Wang Yan, Qingshan Liu, Hanqing Lu, Songde Ma