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» Fisher Kernel Criterion for Discriminant Analysis
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AI
2006
Springer
13 years 11 months ago
On the Performance of Chernoff-Distance-Based Linear Dimensionality Reduction Techniques
Abstract. We present a performance analysis of three linear dimensionality reduction techniques: Fisher's discriminant analysis (FDA), and two methods introduced recently base...
Mohammed Liakat Ali, Luis Rueda, Myriam Herrera
ICPR
2008
IEEE
14 years 1 months ago
IR and visible face recognition using fusion of kernel based features
In this paper we present the face recognition method using feature-level fusion where the infrared (IR) and visible face images are fused at transformed domain. The main contribut...
Shahbe Mat Desa, Subhas Hati
PAMI
2006
132views more  PAMI 2006»
13 years 7 months ago
Capitalize on Dimensionality Increasing Techniques for Improving Face Recognition Grand Challenge Performance
This paper presents a novel pattern recognition framework by capitalizing on dimensionality increasing techniques. In particular, the framework integrates Gabor image representatio...
Chengjun Liu
TNN
2010
234views Management» more  TNN 2010»
13 years 2 months ago
Novel maximum-margin training algorithms for supervised neural networks
This paper proposes three novel training methods, two of them based on the back-propagation approach and a third one based on information theory for Multilayer Perceptron (MLP) bin...
Oswaldo Ludwig, Urbano Nunes
CVPR
2005
IEEE
14 years 9 months ago
Graph Embedding: A General Framework for Dimensionality Reduction
In the last decades, a large family of algorithms supervised or unsupervised; stemming from statistic or geometry theory have been proposed to provide different solutions to the p...
Shuicheng Yan, Dong Xu, Benyu Zhang, HongJiang Zha...